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\n  \n 2025\n \n \n (25)\n \n \n
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\n \n\n \n \n \n \n \n An Evaluation of LLMs and Google Translate for Translation of Selected Indian Languages via Sentiment and Semantic Analyses.\n \n \n \n\n\n \n Chandra, R.; Chaudhari, A.; and Rayavarapu, Y.\n\n\n \n\n\n\n IEEE Access, 13: 122386–122407. 2025.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/access/ChandraCR25,\n  author       = {Rohitash Chandra and\n                  Aryan Chaudhari and\n                  Yeshwanth Rayavarapu},\n  title        = {An Evaluation of LLMs and Google Translate for Translation of Selected\n                  Indian Languages via Sentiment and Semantic Analyses},\n  journal      = {{IEEE} Access},\n  volume       = {13},\n  pages        = {122386--122407},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n HP-BERT: A Framework for Longitudinal Study of Hinduphobia on Social Media via Language Models.\n \n \n \n\n\n \n Singh, A.; and Chandra, R.\n\n\n \n\n\n\n IEEE Access, 13: 175309–175335. 2025.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/access/SinghC25,\n  author       = {Ashutosh Singh and\n                  Rohitash Chandra},\n  title        = {{HP-BERT:} {A} Framework for Longitudinal Study of Hinduphobia on\n                  Social Media via Language Models},\n  journal      = {{IEEE} Access},\n  volume       = {13},\n  pages        = {175309--175335},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n Large language models for newspaper sentiment analysis during COVID-19: The Guardian.\n \n \n \n\n\n \n Chandra, R.; Zhu, B.; Fang, Q.; and Shinjikashvili, E.\n\n\n \n\n\n\n Appl. Soft Comput., 171: 112743. 2025.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/asc/ChandraZFS25,\n  author       = {Rohitash Chandra and\n                  Baicheng Zhu and\n                  Qingying Fang and\n                  Eka Shinjikashvili},\n  title        = {Large language models for newspaper sentiment analysis during {COVID-19:}\n                  The Guardian},\n  journal      = {Appl. Soft Comput.},\n  volume       = {171},\n  pages        = {112743},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n Multi-modal deep learning for credit rating prediction using text and numerical data streams.\n \n \n \n\n\n \n Tavakoli, M.; Chandra, R.; Tian, F.; and Bravo, C.\n\n\n \n\n\n\n Appl. Soft Comput., 171: 112771. 2025.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/asc/TavakoliCTB25,\n  author       = {Mahsa Tavakoli and\n                  Rohitash Chandra and\n                  Fengrui Tian and\n                  Cristi{\\'{a}}n Bravo},\n  title        = {Multi-modal deep learning for credit rating prediction using text\n                  and numerical data streams},\n  journal      = {Appl. Soft Comput.},\n  volume       = {171},\n  pages        = {112771},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n Pedestrian trajectory prediction using goal-driven and dynamics-based deep learning framework.\n \n \n \n\n\n \n Wang, H.; Zhi, W.; Batista, G.; and Chandra, R.\n\n\n \n\n\n\n Expert Syst. Appl., 271: 126557. 2025.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/eswa/WangZBC25,\n  author       = {Honghui Wang and\n                  Weiming Zhi and\n                  Gustavo Batista and\n                  Rohitash Chandra},\n  title        = {Pedestrian trajectory prediction using goal-driven and dynamics-based\n                  deep learning framework},\n  journal      = {Expert Syst. Appl.},\n  volume       = {271},\n  pages        = {126557},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n Multiview graph dual-attention deep learning and contrastive learning for multi-criteria recommender systems.\n \n \n \n\n\n \n Forouzandeh, S.; Krivitsky, P. N.; and Chandra, R.\n\n\n \n\n\n\n Expert Syst. Appl., 291: 128378. 2025.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/eswa/ForouzandehKC25,\n  author       = {Saman Forouzandeh and\n                  Pavel N. Krivitsky and\n                  Rohitash Chandra},\n  title        = {Multiview graph dual-attention deep learning and contrastive learning\n                  for multi-criteria recommender systems},\n  journal      = {Expert Syst. Appl.},\n  volume       = {291},\n  pages        = {128378},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n HP-BERT: A framework for longitudinal study of Hinduphobia on social media via LLMs.\n \n \n \n\n\n \n Singh, A.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2501.05482. 2025.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2501-05482,\n  author       = {Ashutosh Singh and\n                  Rohitash Chandra},\n  title        = {{HP-BERT:} {A} framework for longitudinal study of Hinduphobia on\n                  social media via LLMs},\n  journal      = {CoRR},\n  volume       = {abs/2501.05482},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n Compact Bayesian Neural Networks via pruned MCMC sampling.\n \n \n \n\n\n \n Deo, R.; Sisson, S. A.; Webster, J. M.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2501.06962. 2025.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2501-06962,\n  author       = {Ratneel Deo and\n                  Scott A. Sisson and\n                  Jody M. Webster and\n                  Rohitash Chandra},\n  title        = {Compact Bayesian Neural Networks via pruned {MCMC} sampling},\n  journal      = {CoRR},\n  volume       = {abs/2501.06962},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n A Machine Learning Framework for Handling Unreliable Absence Label and Class Imbalance for Marine Stinger Beaching Prediction.\n \n \n \n\n\n \n Ibenegbu, A.; Schaeffer, A.; de Micheaux, P. L.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2501.11293. 2025.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2501-11293,\n  author       = {Amuche Ibenegbu and\n                  Amandine Schaeffer and\n                  Pierre Lafaye de Micheaux and\n                  Rohitash Chandra},\n  title        = {A Machine Learning Framework for Handling Unreliable Absence Label\n                  and Class Imbalance for Marine Stinger Beaching Prediction},\n  journal      = {CoRR},\n  volume       = {abs/2501.11293},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n Longitudinal Abuse and Sentiment Analysis of Hollywood Movie Dialogues using LLMs.\n \n \n \n\n\n \n Chandra, R.; Ren, G.; and Group-H\n\n\n \n\n\n\n CoRR, abs/2501.13948. 2025.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2501-13948,\n  author       = {Rohitash Chandra and\n                  Guoxiang Ren and\n                  Group{-}H},\n  title        = {Longitudinal Abuse and Sentiment Analysis of Hollywood Movie Dialogues\n                  using LLMs},\n  journal      = {CoRR},\n  volume       = {abs/2501.13948},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n Global Ease of Living Index: a machine learning framework for longitudinal analysis of major economies.\n \n \n \n\n\n \n Panat, T.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2502.06866. 2025.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2502-06866,\n  author       = {Tanay Panat and\n                  Rohitash Chandra},\n  title        = {Global Ease of Living Index: a machine learning framework for longitudinal\n                  analysis of major economies},\n  journal      = {CoRR},\n  volume       = {abs/2502.06866},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n Convolutional neural networks for mineral prospecting through alteration mapping with remote sensing data.\n \n \n \n\n\n \n Farahbakhsh, E.; Goel, D.; Pimparkar, D.; Müller, R. D.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2502.18533. 2025.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2502-18533,\n  author       = {Ehsan Farahbakhsh and\n                  Dakshi Goel and\n                  Dhiraj Pimparkar and\n                  R. Dietmar M{\\"{u}}ller and\n                  Rohitash Chandra},\n  title        = {Convolutional neural networks for mineral prospecting through alteration\n                  mapping with remote sensing data},\n  journal      = {CoRR},\n  volume       = {abs/2502.18533},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n Multiview graph dual-attention deep learning and contrastive learning for multi-criteria recommender systems.\n \n \n \n\n\n \n Forouzandeh, S.; Krivitsky, P. N.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2502.19271. 2025.\n \n\n\n\n
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@article{DBLP:journals/corr/abs-2502-19271,\n  author       = {Saman Forouzandeh and\n                  Pavel N. Krivitsky and\n                  Rohitash Chandra},\n  title        = {Multiview graph dual-attention deep learning and contrastive learning\n                  for multi-criteria recommender systems},\n  journal      = {CoRR},\n  volume       = {abs/2502.19271},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n Research impact evaluation based on effective authorship contribution sensitivity: h-leadership index.\n \n \n \n\n\n \n Jain, H. A.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2503.18236. 2025.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2503-18236,\n  author       = {Hardik A. Jain and\n                  Rohitash Chandra},\n  title        = {Research impact evaluation based on effective authorship contribution\n                  sensitivity: h-leadership index},\n  journal      = {CoRR},\n  volume       = {abs/2503.18236},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n An evaluation of LLMs and Google Translate for translation of selected Indian languages via sentiment and semantic analyses.\n \n \n \n\n\n \n Chandra, R.; Chaudhari, A.; and Rayavarapu, Y.\n\n\n \n\n\n\n CoRR, abs/2503.21393. 2025.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2503-21393,\n  author       = {Rohitash Chandra and\n                  Aryan Chaudhari and\n                  Yeshwanth Rayavarapu},\n  title        = {An evaluation of LLMs and Google Translate for translation of selected\n                  Indian languages via sentiment and semantic analyses},\n  journal      = {CoRR},\n  volume       = {abs/2503.21393},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n Evaluation of LLMs for mathematical problem solving.\n \n \n \n\n\n \n Wang, R.; Wang, R.; Shen, Y.; Wu, C.; Zhou, Q.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2506.00309. 2025.\n \n\n\n\n
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@article{DBLP:journals/corr/abs-2506-00309,\n  author       = {Ruonan Wang and\n                  Runxi Wang and\n                  Yunwen Shen and\n                  Chengfeng Wu and\n                  Qinglin Zhou and\n                  Rohitash Chandra},\n  title        = {Evaluation of LLMs for mathematical problem solving},\n  journal      = {CoRR},\n  volume       = {abs/2506.00309},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n An evaluation of LLMs for generating movie reviews: GPT-4o, Gemini-2.0 and DeepSeek-V3.\n \n \n \n\n\n \n Sands, B.; Wang, Y.; Xu, C.; Zhou, Y.; Wei, L.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2506.00312. 2025.\n \n\n\n\n
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@article{DBLP:journals/corr/abs-2506-00312,\n  author       = {Brendan Sands and\n                  Yining Wang and\n                  Chenhao Xu and\n                  Yuxuan Zhou and\n                  Lai Wei and\n                  Rohitash Chandra},\n  title        = {An evaluation of LLMs for generating movie reviews: GPT-4o, Gemini-2.0\n                  and DeepSeek-V3},\n  journal      = {CoRR},\n  volume       = {abs/2506.00312},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n Spatiotemporal deep learning models for detection of rapid intensification in cyclones.\n \n \n \n\n\n \n Sutar, V.; Singh, A.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2506.08397. 2025.\n \n\n\n\n
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@article{DBLP:journals/corr/abs-2506-08397,\n  author       = {Vamshika Sutar and\n                  Amandeep Singh and\n                  Rohitash Chandra},\n  title        = {Spatiotemporal deep learning models for detection of rapid intensification\n                  in cyclones},\n  journal      = {CoRR},\n  volume       = {abs/2506.08397},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n Abusive text transformation using LLMs.\n \n \n \n\n\n \n Chandra, R.; and Choi, J.\n\n\n \n\n\n\n CoRR, abs/2507.10177. 2025.\n \n\n\n\n
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@article{DBLP:journals/corr/abs-2507-10177,\n  author       = {Rohitash Chandra and\n                  Jiyong Choi},\n  title        = {Abusive text transformation using LLMs},\n  journal      = {CoRR},\n  volume       = {abs/2507.10177},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n Deep learning framework for crater detection and identification on the Moon and Mars.\n \n \n \n\n\n \n Ma, Y.; Yu, Z.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2508.03920. 2025.\n \n\n\n\n
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@article{DBLP:journals/corr/abs-2508-03920,\n  author       = {Yihan Ma and\n                  Zeyang Yu and\n                  Rohitash Chandra},\n  title        = {Deep learning framework for crater detection and identification on\n                  the Moon and Mars},\n  journal      = {CoRR},\n  volume       = {abs/2508.03920},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n Landcover classification and change detection using remote sensing and machine learning: a case study of Western Fiji.\n \n \n \n\n\n \n Gurjar, Y.; Wan, R.; Farahbakhsh, E.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2509.13388. 2025.\n \n\n\n\n
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@article{DBLP:journals/corr/abs-2509-13388,\n  author       = {Yadvendra Gurjar and\n                  Ruoni Wan and\n                  Ehsan Farahbakhsh and\n                  Rohitash Chandra},\n  title        = {Landcover classification and change detection using remote sensing\n                  and machine learning: a case study of Western Fiji},\n  journal      = {CoRR},\n  volume       = {abs/2509.13388},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n Machine Learning for Detection and Analysis of Novel LLM Jailbreaks.\n \n \n \n\n\n \n Hawkins, J.; Pramar, A.; Beard, R.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2510.01644. 2025.\n \n\n\n\n
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@article{DBLP:journals/corr/abs-2510-01644,\n  author       = {John Hawkins and\n                  Aditya Pramar and\n                  Rodney Beard and\n                  Rohitash Chandra},\n  title        = {Machine Learning for Detection and Analysis of Novel {LLM} Jailbreaks},\n  journal      = {CoRR},\n  volume       = {abs/2510.01644},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n Extreme value forecasting using relevance-based data augmentation with deep learning models.\n \n \n \n\n\n \n Hua, J.; Ahluwalia, R.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2510.02407. 2025.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2510-02407,\n  author       = {Junru Hua and\n                  Rahul Ahluwalia and\n                  Rohitash Chandra},\n  title        = {Extreme value forecasting using relevance-based data augmentation\n                  with deep learning models},\n  journal      = {CoRR},\n  volume       = {abs/2510.02407},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n QDeepGR4J: Quantile-based ensemble of deep learning and GR4J hybrid rainfall-runoff models for extreme flow prediction with uncertainty quantification.\n \n \n \n\n\n \n Kapoor, A.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2510.05453. 2025.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2510-05453,\n  author       = {Arpit Kapoor and\n                  Rohitash Chandra},\n  title        = {QDeepGR4J: Quantile-based ensemble of deep learning and {GR4J} hybrid\n                  rainfall-runoff models for extreme flow prediction with uncertainty\n                  quantification},\n  journal      = {CoRR},\n  volume       = {abs/2510.05453},\n  year         = {2025}\n}\n\n
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\n \n\n \n \n \n \n \n Language models for longitudinal analysis of abusive content in Billboard Music Charts.\n \n \n \n\n\n \n Chandra, R.; Suresh, Y.; Sinha, D. R.; and Jindal, S.\n\n\n \n\n\n\n CoRR, abs/2510.06266. 2025.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2510-06266,\n  author       = {Rohitash Chandra and\n                  Yathin Suresh and\n                  Divyansh Raj Sinha and\n                  Sanchit Jindal},\n  title        = {Language models for longitudinal analysis of abusive content in Billboard\n                  Music Charts},\n  journal      = {CoRR},\n  volume       = {abs/2510.06266},\n  year         = {2025}\n}\n\n
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\n  \n 2024\n \n \n (21)\n \n \n
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\n \n\n \n \n \n \n \n ReefCoreSeg: A Clustering-Based Framework for Multi-Source Data Fusion for Segmentation of Reef Drill Cores.\n \n \n \n\n\n \n Deo, R.; Webster, J. M.; Salles, T.; and Chandra, R.\n\n\n \n\n\n\n IEEE Access, 12: 12164–12180. 2024.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/access/DeoWSC24,\n  author       = {Ratneel Deo and\n                  Jody M. Webster and\n                  Tristan Salles and\n                  Rohitash Chandra},\n  title        = {ReefCoreSeg: {A} Clustering-Based Framework for Multi-Source Data\n                  Fusion for Segmentation of Reef Drill Cores},\n  journal      = {{IEEE} Access},\n  volume       = {12},\n  pages        = {12164--12180},\n  year         = {2024}\n}\n\n
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\n \n\n \n \n \n \n \n Bayesian Neural Networks via MCMC: A Python-Based Tutorial.\n \n \n \n\n\n \n Chandra, R.; and Simmons, J. A.\n\n\n \n\n\n\n IEEE Access, 12: 70519–70549. 2024.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/access/ChandraS24,\n  author       = {Rohitash Chandra and\n                  Joshua A. Simmons},\n  title        = {Bayesian Neural Networks via {MCMC:} {A} Python-Based Tutorial},\n  journal      = {{IEEE} Access},\n  volume       = {12},\n  pages        = {70519--70549},\n  year         = {2024}\n}\n\n
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\n \n\n \n \n \n \n \n Large Language Models for Metaphor Detection: Bhagavad Gita and Sermon on the Mount.\n \n \n \n\n\n \n Chandra, R.; Tiwari, A.; Jain, N.; and Badhe, S.\n\n\n \n\n\n\n IEEE Access, 12: 84452–84469. 2024.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/access/ChandraTJB24,\n  author       = {Rohitash Chandra and\n                  Abhishek Tiwari and\n                  Naman Jain and\n                  Sushrut Badhe},\n  title        = {Large Language Models for Metaphor Detection: Bhagavad Gita and Sermon\n                  on the Mount},\n  journal      = {{IEEE} Access},\n  volume       = {12},\n  pages        = {84452--84469},\n  year         = {2024}\n}\n\n
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\n \n\n \n \n \n \n \n Recursive Deep Learning Framework for Forecasting the Decadal World Economic Outlook.\n \n \n \n\n\n \n Wang, T.; Beard, R.; Hawkins, J.; and Chandra, R.\n\n\n \n\n\n\n IEEE Access, 12: 152921–152944. 2024.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/access/WangBHC24,\n  author       = {Tianyi Wang and\n                  Rodney Beard and\n                  John Hawkins and\n                  Rohitash Chandra},\n  title        = {Recursive Deep Learning Framework for Forecasting the Decadal World\n                  Economic Outlook},\n  journal      = {{IEEE} Access},\n  volume       = {12},\n  pages        = {152921--152944},\n  year         = {2024}\n}\n\n
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\n \n\n \n \n \n \n \n A Quantum-Inspired Predator-Prey Algorithm for Real-Parameter Optimization.\n \n \n \n\n\n \n Khan, A. A.; Hussain, S.; and Chandra, R.\n\n\n \n\n\n\n Algorithms, 17(1): 33. 2024.\n \n\n\n\n
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@article{DBLP:journals/algorithms/KhanHC24,\n  author       = {Azal Ahmad Khan and\n                  Salman Hussain and\n                  Rohitash Chandra},\n  title        = {A Quantum-Inspired Predator-Prey Algorithm for Real-Parameter Optimization},\n  journal      = {Algorithms},\n  volume       = {17},\n  number       = {1},\n  pages        = {33},\n  year         = {2024}\n}\n\n
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\n \n\n \n \n \n \n \n A unified machine learning framework for basketball team roster construction: NBA and WNBA.\n \n \n \n\n\n \n Ke, Y.; Bian, R.; and Chandra, R.\n\n\n \n\n\n\n Appl. Soft Comput., 153: 111298. 2024.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/asc/KeBC24,\n  author       = {Yuhao Ke and\n                  Ranran Bian and\n                  Rohitash Chandra},\n  title        = {A unified machine learning framework for basketball team roster construction:\n                  {NBA} and {WNBA}},\n  journal      = {Appl. Soft Comput.},\n  volume       = {153},\n  pages        = {111298},\n  year         = {2024}\n}\n\n
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\n \n\n \n \n \n \n \n An Analysis of Vaccine-Related Sentiments on Twitter (X) from Development to Deployment of COVID-19 Vaccines.\n \n \n \n\n\n \n Chandra, R.; Sonawane, J.; and Lande, J.\n\n\n \n\n\n\n Big Data Cogn. Comput., 8(12): 186. 2024.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/bdcc/ChandraSL24,\n  author       = {Rohitash Chandra and\n                  Jayesh Sonawane and\n                  Jahnavi Lande},\n  title        = {An Analysis of Vaccine-Related Sentiments on Twitter {(X)} from Development\n                  to Deployment of {COVID-19} Vaccines},\n  journal      = {Big Data Cogn. Comput.},\n  volume       = {8},\n  number       = {12},\n  pages        = {186},\n  year         = {2024}\n}\n\n
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\n \n\n \n \n \n \n \n Deep learning framework with Bayesian data imputation for modelling and forecasting groundwater levels.\n \n \n \n\n\n \n Chen, E.; Andersen, M. S.; and Chandra, R.\n\n\n \n\n\n\n Environ. Model. Softw., 178: 106072. 2024.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/envsoft/ChenAC24,\n  author       = {Eric Chen and\n                  Martin S. Andersen and\n                  Rohitash Chandra},\n  title        = {Deep learning framework with Bayesian data imputation for modelling\n                  and forecasting groundwater levels},\n  journal      = {Environ. Model. Softw.},\n  volume       = {178},\n  pages        = {106072},\n  year         = {2024}\n}\n\n
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\n \n\n \n \n \n \n \n A review of ensemble learning and data augmentation models for class imbalanced problems: Combination, implementation and evaluation.\n \n \n \n\n\n \n Khan, A. A.; Chaudhari, O.; and Chandra, R.\n\n\n \n\n\n\n Expert Syst. Appl., 244: 122778. 2024.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/eswa/KhanCC24,\n  author       = {Azal Ahmad Khan and\n                  Omkar Chaudhari and\n                  Rohitash Chandra},\n  title        = {A review of ensemble learning and data augmentation models for class\n                  imbalanced problems: Combination, implementation and evaluation},\n  journal      = {Expert Syst. Appl.},\n  volume       = {244},\n  pages        = {122778},\n  year         = {2024}\n}\n\n
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\n \n\n \n \n \n \n \n A clustering and graph deep learning-based framework for COVID-19 drug repurposing.\n \n \n \n\n\n \n Bansal, C.; Deepa, P. R.; Agarwal, V.; and Chandra, R.\n\n\n \n\n\n\n Expert Syst. Appl., 249: 123560. 2024.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/eswa/BansalDAC24,\n  author       = {Chaarvi Bansal and\n                  P. R. Deepa and\n                  Vinti Agarwal and\n                  Rohitash Chandra},\n  title        = {A clustering and graph deep learning-based framework for {COVID-19}\n                  drug repurposing},\n  journal      = {Expert Syst. Appl.},\n  volume       = {249},\n  pages        = {123560},\n  year         = {2024}\n}\n\n
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\n \n\n \n \n \n \n \n Sequential reversible jump MCMC for dynamic Bayesian neural networks.\n \n \n \n\n\n \n Nguyen, N. M.; Tran, M.; and Chandra, R.\n\n\n \n\n\n\n Neurocomputing, 564: 126960. 2024.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/ijon/NguyenTC24,\n  author       = {Nhat Minh Nguyen and\n                  Minh{-}Ngoc Tran and\n                  Rohitash Chandra},\n  title        = {Sequential reversible jump {MCMC} for dynamic Bayesian neural networks},\n  journal      = {Neurocomputing},\n  volume       = {564},\n  pages        = {126960},\n  year         = {2024}\n}\n\n
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\n \n\n \n \n \n \n \n Pedestrian Trajectory Prediction Using Dynamics-based Deep Learning.\n \n \n \n\n\n \n Wang, H.; Zhi, W.; Batista, G.; and Chandra, R.\n\n\n \n\n\n\n In ICRA, pages 15068–15075, 2024. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/icra/WangZBC24,\n  author       = {Honghui Wang and\n                  Weiming Zhi and\n                  Gustavo Batista and\n                  Rohitash Chandra},\n  title        = {Pedestrian Trajectory Prediction Using Dynamics-based Deep Learning},\n  booktitle    = {{ICRA}},\n  pages        = {15068--15075},\n  publisher    = {{IEEE}},\n  year         = {2024}\n}\n\n
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\n \n\n \n \n \n \n \n Large language model for Bible sentiment analysis: Sermon on the Mount.\n \n \n \n\n\n \n Vora, M.; Blau, T.; Kachhwal, V.; Solo, A. M. G.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2401.00689. 2024.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2401-00689,\n  author       = {Mahek Vora and\n                  Tom Blau and\n                  Vansh Kachhwal and\n                  Ashu M. G. Solo and\n                  Rohitash Chandra},\n  title        = {Large language model for Bible sentiment analysis: Sermon on the Mount},\n  journal      = {CoRR},\n  volume       = {abs/2401.00689},\n  year         = {2024}\n}\n\n
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\n \n\n \n \n \n \n \n Self-supervised learning for skin cancer diagnosis with limited training data.\n \n \n \n\n\n \n Haggerty, H.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2401.00692. 2024.\n \n\n\n\n
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@article{DBLP:journals/corr/abs-2401-00692,\n  author       = {Hamish Haggerty and\n                  Rohitash Chandra},\n  title        = {Self-supervised learning for skin cancer diagnosis with limited training\n                  data},\n  journal      = {CoRR},\n  volume       = {abs/2401.00692},\n  year         = {2024}\n}\n\n
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\n \n\n \n \n \n \n \n Remote sensing framework for geological mapping via stacked autoencoders and clustering.\n \n \n \n\n\n \n Nagar, S.; Farahbakhsh, E.; Awange, J. L.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2404.02180. 2024.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2404-02180,\n  author       = {Sandeep Nagar and\n                  Ehsan Farahbakhsh and\n                  Joseph L. Awange and\n                  Rohitash Chandra},\n  title        = {Remote sensing framework for geological mapping via stacked autoencoders\n                  and clustering},\n  journal      = {CoRR},\n  volume       = {abs/2404.02180},\n  year         = {2024}\n}\n\n
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\n \n\n \n \n \n \n \n Large language models for sentiment analysis of newspaper articles during COVID-19: The Guardian.\n \n \n \n\n\n \n Chandra, R.; Zhu, B.; Fang, Q.; and Shinjikashvili, E.\n\n\n \n\n\n\n CoRR, abs/2405.13056. 2024.\n \n\n\n\n
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@article{DBLP:journals/corr/abs-2405-13056,\n  author       = {Rohitash Chandra and\n                  Baicheng Zhu and\n                  Qingying Fang and\n                  Eka Shinjikashvili},\n  title        = {Large language models for sentiment analysis of newspaper articles\n                  during {COVID-19:} The Guardian},\n  journal      = {CoRR},\n  volume       = {abs/2405.13056},\n  year         = {2024}\n}\n\n
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\n \n\n \n \n \n \n \n Evaluation of deep learning models for Australian climate extremes: prediction of streamflow and floods.\n \n \n \n\n\n \n Khedkar, S.; Vervoort, R. W.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2407.15882. 2024.\n \n\n\n\n
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@article{DBLP:journals/corr/abs-2407-15882,\n  author       = {Siddharth Khedkar and\n                  R. Willem Vervoort and\n                  Rohitash Chandra},\n  title        = {Evaluation of deep learning models for Australian climate extremes:\n                  prediction of streamflow and floods},\n  journal      = {CoRR},\n  volume       = {abs/2407.15882},\n  year         = {2024}\n}\n\n
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\n \n\n \n \n \n \n \n A longitudinal sentiment analysis of Sinophobia during COVID-19 using large language models.\n \n \n \n\n\n \n Wang, C.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2408.16942. 2024.\n \n\n\n\n
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@article{DBLP:journals/corr/abs-2408-16942,\n  author       = {Chen Wang and\n                  Rohitash Chandra},\n  title        = {A longitudinal sentiment analysis of Sinophobia during {COVID-19}\n                  using large language models},\n  journal      = {CoRR},\n  volume       = {abs/2408.16942},\n  year         = {2024}\n}\n\n
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\n \n\n \n \n \n \n \n Evaluation of Google Translate for Mandarin Chinese translation using sentiment and semantic analysis.\n \n \n \n\n\n \n Wang, X.; Beard, R.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2409.04964. 2024.\n \n\n\n\n
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@article{DBLP:journals/corr/abs-2409-04964,\n  author       = {Xuechun Wang and\n                  Rodney Beard and\n                  Rohitash Chandra},\n  title        = {Evaluation of Google Translate for Mandarin Chinese translation using\n                  sentiment and semantic analysis},\n  journal      = {CoRR},\n  volume       = {abs/2409.04964},\n  year         = {2024}\n}\n\n
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\n \n\n \n \n \n \n \n Bayes-CATSI: A variational Bayesian deep learning framework for medical time series data imputation.\n \n \n \n\n\n \n Kulkarni, O.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2410.01847. 2024.\n \n\n\n\n
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@article{DBLP:journals/corr/abs-2410-01847,\n  author       = {Omkar Kulkarni and\n                  Rohitash Chandra},\n  title        = {Bayes-CATSI: {A} variational Bayesian deep learning framework for\n                  medical time series data imputation},\n  journal      = {CoRR},\n  volume       = {abs/2410.01847},\n  year         = {2024}\n}\n\n
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\n \n\n \n \n \n \n \n Quantile deep learning models for multi-step ahead time series prediction.\n \n \n \n\n\n \n Cheung, J.; Rangarajan, S.; Maddocks, A.; Chen, X.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2411.15674. 2024.\n \n\n\n\n
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@article{DBLP:journals/corr/abs-2411-15674,\n  author       = {Jimmy Cheung and\n                  Smruthi Rangarajan and\n                  Amelia Maddocks and\n                  Xizhe Chen and\n                  Rohitash Chandra},\n  title        = {Quantile deep learning models for multi-step ahead time series prediction},\n  journal      = {CoRR},\n  volume       = {abs/2411.15674},\n  year         = {2024}\n}\n\n
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\n \n\n \n \n \n \n \n Physics-informed neural entangled-ladder network for inhalation impedance of the respiratory system.\n \n \n \n\n\n \n Kumar, A. K.; Jain, S.; Jain, S.; Ritam, M.; Xia, Y.; and Chandra, R.\n\n\n \n\n\n\n Comput. Methods Programs Biomed., 231: 107421. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/cmpb/KumarJJRXC23,\n  author       = {Amit Krishan Kumar and\n                  Snigdha Jain and\n                  Shirin Jain and\n                  M. Ritam and\n                  Yuanqing Xia and\n                  Rohitash Chandra},\n  title        = {Physics-informed neural entangled-ladder network for inhalation impedance\n                  of the respiratory system},\n  journal      = {Comput. Methods Programs Biomed.},\n  volume       = {231},\n  pages        = {107421},\n  year         = {2023}\n}\n\n
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\n \n\n \n \n \n \n \n Cyclone trajectory and intensity prediction with uncertainty quantification using variational recurrent neural networks.\n \n \n \n\n\n \n Kapoor, A.; Negi, A.; Marshall, L. A.; and Chandra, R.\n\n\n \n\n\n\n Environ. Model. Softw., 162: 105654. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/envsoft/KapoorNMC23,\n  author       = {Arpit Kapoor and\n                  Anshul Negi and\n                  Lucy A. Marshall and\n                  Rohitash Chandra},\n  title        = {Cyclone trajectory and intensity prediction with uncertainty quantification\n                  using variational recurrent neural networks},\n  journal      = {Environ. Model. Softw.},\n  volume       = {162},\n  pages        = {105654},\n  year         = {2023}\n}\n\n
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\n \n\n \n \n \n \n \n DeepGR4J: A deep learning hybridization approach for conceptual rainfall-runoff modelling.\n \n \n \n\n\n \n Kapoor, A.; Pathiraja, S.; Marshall, L. A.; and Chandra, R.\n\n\n \n\n\n\n Environ. Model. Softw., 169: 105831. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/envsoft/KapoorPMC23,\n  author       = {Arpit Kapoor and\n                  Sahani Pathiraja and\n                  Lucy A. Marshall and\n                  Rohitash Chandra},\n  title        = {DeepGR4J: {A} deep learning hybridization approach for conceptual\n                  rainfall-runoff modelling},\n  journal      = {Environ. Model. Softw.},\n  volume       = {169},\n  pages        = {105831},\n  year         = {2023}\n}\n\n
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\n \n\n \n \n \n \n \n Gradient boosting Bayesian neural networks via Langevin MCMC.\n \n \n \n\n\n \n Bai, G.; and Chandra, R.\n\n\n \n\n\n\n Neurocomputing, 558: 126726. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/ijon/BaiC23,\n  author       = {George Bai and\n                  Rohitash Chandra},\n  title        = {Gradient boosting Bayesian neural networks via Langevin {MCMC}},\n  journal      = {Neurocomputing},\n  volume       = {558},\n  pages        = {126726},\n  year         = {2023}\n}\n\n
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\n \n\n \n \n \n \n \n Memory capacity of recurrent neural networks with matrix representation.\n \n \n \n\n\n \n Renanse, A.; Sharma, A.; and Chandra, R.\n\n\n \n\n\n\n Neurocomputing, 560: 126824. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/ijon/RenanseSC23,\n  author       = {Animesh Renanse and\n                  Alok Sharma and\n                  Rohitash Chandra},\n  title        = {Memory capacity of recurrent neural networks with matrix representation},\n  journal      = {Neurocomputing},\n  volume       = {560},\n  pages        = {126824},\n  year         = {2023}\n}\n\n
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\n \n\n \n \n \n \n \n Reef-Insight: A Framework for Reef Habitat Mapping with Clustering Methods Using Remote Sensing.\n \n \n \n\n\n \n Barve, S.; Webster, J. M.; and Chandra, R.\n\n\n \n\n\n\n Inf., 14(7): 373. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/information/BarveWC23,\n  author       = {Saharsh Barve and\n                  Jody M. Webster and\n                  Rohitash Chandra},\n  title        = {Reef-Insight: {A} Framework for Reef Habitat Mapping with Clustering\n                  Methods Using Remote Sensing},\n  journal      = {Inf.},\n  volume       = {14},\n  number       = {7},\n  pages        = {373},\n  year         = {2023}\n}\n\n
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\n \n\n \n \n \n \n \n An evaluation of Google Translate for Sanskrit to English translation via sentiment and semantic analysis.\n \n \n \n\n\n \n Shukla, A.; Bansal, C.; Badhe, S.; Ranjan, M.; and Chandra, R.\n\n\n \n\n\n\n Nat. Lang. Process. J., 4: 100025. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/nlpj/ShuklaBBRC23,\n  author       = {Akshat Shukla and\n                  Chaarvi Bansal and\n                  Sushrut Badhe and\n                  Mukul Ranjan and\n                  Rohitash Chandra},\n  title        = {An evaluation of Google Translate for Sanskrit to English translation\n                  via sentiment and semantic analysis},\n  journal      = {Nat. Lang. Process. J.},\n  volume       = {4},\n  pages        = {100025},\n  year         = {2023}\n}\n\n
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\n \n\n \n \n \n \n \n Recursive deep learning framework for forecasting the decadal world economic outlook.\n \n \n \n\n\n \n Wang, T.; Beard, R.; Hawkins, J.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2301.10874. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2301-10874,\n  author       = {Tianyi Wang and\n                  Rodney Beard and\n                  John Hawkins and\n                  Rohitash Chandra},\n  title        = {Recursive deep learning framework for forecasting the decadal world\n                  economic outlook},\n  journal      = {CoRR},\n  volume       = {abs/2301.10874},\n  year         = {2023}\n}\n\n
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\n \n\n \n \n \n \n \n Reef-insight: A framework for reef habitat mapping with clustering methods via remote sensing.\n \n \n \n\n\n \n Barve, S.; Webster, J. M.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2301.10876. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2301-10876,\n  author       = {Saharsh Barve and\n                  Jody M. Webster and\n                  Rohitash Chandra},\n  title        = {Reef-insight: {A} framework for reef habitat mapping with clustering\n                  methods via remote sensing},\n  journal      = {CoRR},\n  volume       = {abs/2301.10876},\n  year         = {2023}\n}\n\n
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\n \n\n \n \n \n \n \n Deep learning for COVID-19 topic modelling via Twitter: Alpha, Delta and Omicron.\n \n \n \n\n\n \n Lande, J.; Pillay, A.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2303.00135. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2303-00135,\n  author       = {Janhavi Lande and\n                  Arti Pillay and\n                  Rohitash Chandra},\n  title        = {Deep learning for {COVID-19} topic modelling via Twitter: Alpha, Delta\n                  and Omicron},\n  journal      = {CoRR},\n  volume       = {abs/2303.00135},\n  year         = {2023}\n}\n\n
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\n \n\n \n \n \n \n \n An evaluation of Google Translate for Sanskrit to English translation via sentiment and semantic analysis.\n \n \n \n\n\n \n Shukla, A.; Bansal, C.; Badhe, S.; Ranjan, M.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2303.07201. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2303-07201,\n  author       = {Akshat Shukla and\n                  Chaarvi Bansal and\n                  Sushrut Badhe and\n                  Mukul Ranjan and\n                  Rohitash Chandra},\n  title        = {An evaluation of Google Translate for Sanskrit to English translation\n                  via sentiment and semantic analysis},\n  journal      = {CoRR},\n  volume       = {abs/2303.07201},\n  year         = {2023}\n}\n\n
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\n \n\n \n \n \n \n \n Bayesian neural networks via MCMC: a Python-based tutorial.\n \n \n \n\n\n \n Chandra, R.; Chen, R.; and Simmons, J. A.\n\n\n \n\n\n\n CoRR, abs/2304.02595. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2304-02595,\n  author       = {Rohitash Chandra and\n                  Royce Chen and\n                  Joshua A. Simmons},\n  title        = {Bayesian neural networks via {MCMC:} a Python-based tutorial},\n  journal      = {CoRR},\n  volume       = {abs/2304.02595},\n  year         = {2023}\n}\n\n
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\n \n\n \n \n \n \n \n A review of ensemble learning and data augmentation models for class imbalanced problems: combination, implementation and evaluation.\n \n \n \n\n\n \n Khan, A. A.; Chaudhari, O.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2304.02858. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2304-02858,\n  author       = {Azal Ahmad Khan and\n                  Omkar Chaudhari and\n                  Rohitash Chandra},\n  title        = {A review of ensemble learning and data augmentation models for class\n                  imbalanced problems: combination, implementation and evaluation},\n  journal      = {CoRR},\n  volume       = {abs/2304.02858},\n  year         = {2023}\n}\n\n
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\n \n\n \n \n \n \n \n Multi-Modal Deep Learning for Credit Rating Prediction Using Text and Numerical Data Streams.\n \n \n \n\n\n \n Tavakoli, M.; Chandra, R.; Tian, F.; and Bravo, C.\n\n\n \n\n\n\n CoRR, abs/2304.10740. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2304-10740,\n  author       = {Mahsa Tavakoli and\n                  Rohitash Chandra and\n                  Fengrui Tian and\n                  Cristi{\\'{a}}n Bravo},\n  title        = {Multi-Modal Deep Learning for Credit Rating Prediction Using Text\n                  and Numerical Data Streams},\n  journal      = {CoRR},\n  volume       = {abs/2304.10740},\n  year         = {2023}\n}\n\n
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\n \n\n \n \n \n \n \n An analysis of vaccine-related sentiments from development to deployment of COVID-19 vaccines.\n \n \n \n\n\n \n Chandra, R.; Sonawane, J.; Lande, J.; and Yu, C.\n\n\n \n\n\n\n CoRR, abs/2306.13797. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2306-13797,\n  author       = {Rohitash Chandra and\n                  Jayesh Sonawane and\n                  Janhavi Lande and\n                  Cathy Yu},\n  title        = {An analysis of vaccine-related sentiments from development to deployment\n                  of {COVID-19} vaccines},\n  journal      = {CoRR},\n  volume       = {abs/2306.13797},\n  year         = {2023}\n}\n\n
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\n \n\n \n \n \n \n \n A clustering and graph deep learning-based framework for COVID-19 drug repurposing.\n \n \n \n\n\n \n Bansal, C.; Chandra, R.; Agarwal, V.; and Deepa, P. R.\n\n\n \n\n\n\n CoRR, abs/2306.13995. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2306-13995,\n  author       = {Chaarvi Bansal and\n                  Rohitash Chandra and\n                  Vinti Agarwal and\n                  P. R. Deepa},\n  title        = {A clustering and graph deep learning-based framework for {COVID-19}\n                  drug repurposing},\n  journal      = {CoRR},\n  volume       = {abs/2306.13995},\n  year         = {2023}\n}\n\n
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\n \n\n \n \n \n \n \n Pedestrian Trajectory Prediction Using Dynamics-based Deep Learning.\n \n \n \n\n\n \n Wang, H.; Zhi, W.; Batista, G.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2309.09021. 2023.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2309-09021,\n  author       = {Honghui Wang and\n                  Weiming Zhi and\n                  Gustavo Batista and\n                  Rohitash Chandra},\n  title        = {Pedestrian Trajectory Prediction Using Dynamics-based Deep Learning},\n  journal      = {CoRR},\n  volume       = {abs/2309.09021},\n  year         = {2023}\n}\n\n
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\n  \n 2022\n \n \n (15)\n \n \n
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\n \n\n \n \n \n \n \n Semantic and Sentiment Analysis of Selected Bhagavad Gita Translations Using BERT-Based Language Framework.\n \n \n \n\n\n \n Chandra, R.; and Kulkarni, V.\n\n\n \n\n\n\n IEEE Access, 10: 21291–21315. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/access/ChandraK22,\n  author       = {Rohitash Chandra and\n                  Venkatesh Kulkarni},\n  title        = {Semantic and Sentiment Analysis of Selected Bhagavad Gita Translations\n                  Using BERT-Based Language Framework},\n  journal      = {{IEEE} Access},\n  volume       = {10},\n  pages        = {21291--21315},\n  year         = {2022}\n}\n\n
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\n \n\n \n \n \n \n \n SMOTified-GAN for Class Imbalanced Pattern Classification Problems.\n \n \n \n\n\n \n Sharma, A.; Singh, P. K.; and Chandra, R.\n\n\n \n\n\n\n IEEE Access, 10: 30655–30665. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/access/SharmaSC22,\n  author       = {Anuraganand Sharma and\n                  Prabhat Kumar Singh and\n                  Rohitash Chandra},\n  title        = {SMOTified-GAN for Class Imbalanced Pattern Classification Problems},\n  journal      = {{IEEE} Access},\n  volume       = {10},\n  pages        = {30655--30665},\n  year         = {2022}\n}\n\n
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\n \n\n \n \n \n \n \n Revisiting Bayesian Autoencoders With MCMC.\n \n \n \n\n\n \n Chandra, R.; Jain, M.; Maharana, M.; and Krivitsky, P. N.\n\n\n \n\n\n\n IEEE Access, 10: 40482–40495. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/access/ChandraJMK22,\n  author       = {Rohitash Chandra and\n                  Mahir Jain and\n                  Manavendra Maharana and\n                  Pavel N. Krivitsky},\n  title        = {Revisiting Bayesian Autoencoders With {MCMC}},\n  journal      = {{IEEE} Access},\n  volume       = {10},\n  pages        = {40482--40495},\n  year         = {2022}\n}\n\n
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\n \n\n \n \n \n \n \n Bayesian neuroevolution using distributed swarm optimization and tempered MCMC.\n \n \n \n\n\n \n Kapoor, A.; Nukala, E.; and Chandra, R.\n\n\n \n\n\n\n Appl. Soft Comput., 129: 109528. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/asc/KapoorNC22,\n  author       = {Arpit Kapoor and\n                  Eshwar Nukala and\n                  Rohitash Chandra},\n  title        = {Bayesian neuroevolution using distributed swarm optimization and tempered\n                  {MCMC}},\n  journal      = {Appl. Soft Comput.},\n  volume       = {129},\n  pages        = {109528},\n  year         = {2022}\n}\n\n
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\n \n\n \n \n \n \n \n Deep learning for predicting respiratory rate from biosignals.\n \n \n \n\n\n \n Kumar, A. K.; Ritam, M.; Han, L.; Guo, S.; and Chandra, R.\n\n\n \n\n\n\n Comput. Biol. Medicine, 144: 105338. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/cbm/KumarRHGC22,\n  author       = {Amit Krishan Kumar and\n                  M. Ritam and\n                  Lina Han and\n                  Shuli Guo and\n                  Rohitash Chandra},\n  title        = {Deep learning for predicting respiratory rate from biosignals},\n  journal      = {Comput. Biol. Medicine},\n  volume       = {144},\n  pages        = {105338},\n  year         = {2022}\n}\n\n
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\n \n\n \n \n \n \n \n CoviRx: A User-Friendly Interface for Systematic Down-Selection of Repurposed Drug Candidates for COVID-19.\n \n \n \n\n\n \n Jain, H. A.; Agarwal, V.; Bansal, C.; Kumar, A.; Faheem, F.; Mohammed, M.; Murugesan, S.; Simpson, M. M.; Karpe, A. V.; Chandra, R.; MacRaild, C. A.; Styles, I. K.; Peterson, A. L.; Cooper, M. A.; Kirkpatrick, C. M. J.; Shah, R. M.; Palombo, E. A.; Trevaskis, N. L.; Creek, D. J.; and Vasan, S. S.\n\n\n \n\n\n\n Data, 7(11): 164. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/data/JainABKFMMSKCMS22,\n  author       = {Hardik A. Jain and\n                  Vinti Agarwal and\n                  Chaarvi Bansal and\n                  Anupama Kumar and\n                  Faheem Faheem and\n                  Muzaffar{-}Ur{-}Rehman Mohammed and\n                  Sankaranarayanan Murugesan and\n                  Moana M. Simpson and\n                  Avinash V. Karpe and\n                  Rohitash Chandra and\n                  Christopher A. MacRaild and\n                  Ian K. Styles and\n                  Amanda L. Peterson and\n                  Matthew A. Cooper and\n                  Carl M. J. Kirkpatrick and\n                  Rohan M. Shah and\n                  Enzo A. Palombo and\n                  Natalie L. Trevaskis and\n                  Darren J. Creek and\n                  Seshadri S. Vasan},\n  title        = {CoviRx: {A} User-Friendly Interface for Systematic Down-Selection\n                  of Repurposed Drug Candidates for {COVID-19}},\n  journal      = {Data},\n  volume       = {7},\n  number       = {11},\n  pages        = {164},\n  year         = {2022}\n}\n\n
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\n \n\n \n \n \n \n \n Distributed Bayesian optimisation framework for deep neuroevolution.\n \n \n \n\n\n \n Chandra, R.; and Tiwari, A.\n\n\n \n\n\n\n Neurocomputing, 470: 51–65. 2022.\n \n\n\n\n
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@article{DBLP:journals/ijon/ChandraT22,\n  author       = {Rohitash Chandra and\n                  Animesh Tiwari},\n  title        = {Distributed Bayesian optimisation framework for deep neuroevolution},\n  journal      = {Neurocomputing},\n  volume       = {470},\n  pages        = {51--65},\n  year         = {2022}\n}\n\n
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\n \n\n \n \n \n \n \n Evolutionary bagging for ensemble learning.\n \n \n \n\n\n \n Ngo, G.; Beard, R.; and Chandra, R.\n\n\n \n\n\n\n Neurocomputing, 510: 1–14. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/ijon/NgoBC22,\n  author       = {Giang Ngo and\n                  Rodney Beard and\n                  Rohitash Chandra},\n  title        = {Evolutionary bagging for ensemble learning},\n  journal      = {Neurocomputing},\n  volume       = {510},\n  pages        = {1--14},\n  year         = {2022}\n}\n\n
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\n \n\n \n \n \n \n \n A Comparative Study of Convolutional Neural Networks and Conventional Machine Learning Models for Lithological Mapping Using Remote Sensing Data.\n \n \n \n\n\n \n Shirmard, H.; Farahbakhsh, E.; Heidari, E.; Pour, A. B.; Pradhan, B.; Müller, R. D.; and Chandra, R.\n\n\n \n\n\n\n Remote. Sens., 14(4): 819. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/remotesensing/ShirmardFHPPMC22,\n  author       = {Hodjat Shirmard and\n                  Ehsan Farahbakhsh and\n                  Elnaz Heidari and\n                  Amin Beiranvand Pour and\n                  Biswajeet Pradhan and\n                  R. Dietmar M{\\"{u}}ller and\n                  Rohitash Chandra},\n  title        = {A Comparative Study of Convolutional Neural Networks and Conventional\n                  Machine Learning Models for Lithological Mapping Using Remote Sensing\n                  Data},\n  journal      = {Remote. Sens.},\n  volume       = {14},\n  number       = {4},\n  pages        = {819},\n  year         = {2022}\n}\n\n
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\n \n\n \n \n \n \n \n Semantic and sentiment analysis of selected Bhagavad Gita translations using BERT-based language framework.\n \n \n \n\n\n \n Chandra, R.; and Kulkarni, V.\n\n\n \n\n\n\n CoRR, abs/2201.03115. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2201-03115,\n  author       = {Rohitash Chandra and\n                  Venkatesh Kulkarni},\n  title        = {Semantic and sentiment analysis of selected Bhagavad Gita translations\n                  using BERT-based language framework},\n  journal      = {CoRR},\n  volume       = {abs/2201.03115},\n  year         = {2022}\n}\n\n
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\n \n\n \n \n \n \n \n Surrogate-assisted distributed swarm optimisation for computationally expensive models.\n \n \n \n\n\n \n Chandra, R.; and Sharma, Y. V.\n\n\n \n\n\n\n CoRR, abs/2201.06843. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2201-06843,\n  author       = {Rohitash Chandra and\n                  Yash Vardhan Sharma},\n  title        = {Surrogate-assisted distributed swarm optimisation for computationally\n                  expensive models},\n  journal      = {CoRR},\n  volume       = {abs/2201.06843},\n  year         = {2022}\n}\n\n
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\n \n\n \n \n \n \n \n MAP-Elites based Hyper-Heuristic for the Resource Constrained Project Scheduling Problem.\n \n \n \n\n\n \n Chand, S.; Rajesh, K.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2204.11162. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2204-11162,\n  author       = {Shelvin Chand and\n                  Kousik Rajesh and\n                  Rohitash Chandra},\n  title        = {MAP-Elites based Hyper-Heuristic for the Resource Constrained Project\n                  Scheduling Problem},\n  journal      = {CoRR},\n  volume       = {abs/2204.11162},\n  year         = {2022}\n}\n\n
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\n \n\n \n \n \n \n \n Artificial intelligence for topic modelling in Hindu philosophy: mapping themes between the Upanishads and the Bhagavad Gita.\n \n \n \n\n\n \n Chandra, R.; and Ranjan, M.\n\n\n \n\n\n\n CoRR, abs/2205.11020. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2205-11020,\n  author       = {Rohitash Chandra and\n                  Mukul Ranjan},\n  title        = {Artificial intelligence for topic modelling in Hindu philosophy: mapping\n                  themes between the Upanishads and the Bhagavad Gita},\n  journal      = {CoRR},\n  volume       = {abs/2205.11020},\n  year         = {2022}\n}\n\n
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\n \n\n \n \n \n \n \n Unsupervised machine learning framework for discriminating major variants of concern during COVID-19.\n \n \n \n\n\n \n Kang, M.; Vasan, S.; Wilson, L. O. W.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2208.01439. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2208-01439,\n  author       = {Mingyue Kang and\n                  Seshadri Vasan and\n                  Laurence O. W. Wilson and\n                  Rohitash Chandra},\n  title        = {Unsupervised machine learning framework for discriminating major variants\n                  of concern during {COVID-19}},\n  journal      = {CoRR},\n  volume       = {abs/2208.01439},\n  year         = {2022}\n}\n\n
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\n \n\n \n \n \n \n \n Evolutionary bagging for ensemble learning.\n \n \n \n\n\n \n Ngo, G.; Beard, R.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2208.02400. 2022.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2208-02400,\n  author       = {Giang Ngo and\n                  Rodney Beard and\n                  Rohitash Chandra},\n  title        = {Evolutionary bagging for ensemble learning},\n  journal      = {CoRR},\n  volume       = {abs/2208.02400},\n  year         = {2022}\n}\n\n
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\n  \n 2021\n \n \n (13)\n \n \n
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\n \n\n \n \n \n \n \n Evaluation of Deep Learning Models for Multi-Step Ahead Time Series Prediction.\n \n \n \n\n\n \n Chandra, R.; Goyal, S.; and Gupta, R.\n\n\n \n\n\n\n IEEE Access, 9: 83105–83123. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/access/ChandraGG21,\n  author       = {Rohitash Chandra and\n                  Shaurya Goyal and\n                  Rishabh Gupta},\n  title        = {Evaluation of Deep Learning Models for Multi-Step Ahead Time Series\n                  Prediction},\n  journal      = {{IEEE} Access},\n  volume       = {9},\n  pages        = {83105--83123},\n  year         = {2021}\n}\n\n
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\n \n\n \n \n \n \n \n Biden vs Trump: Modeling US General Elections Using BERT Language Model.\n \n \n \n\n\n \n Chandra, R.; and Saini, R.\n\n\n \n\n\n\n IEEE Access, 9: 128494–128505. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/access/ChandraS21,\n  author       = {Rohitash Chandra and\n                  Ritij Saini},\n  title        = {Biden vs Trump: Modeling {US} General Elections Using {BERT} Language\n                  Model},\n  journal      = {{IEEE} Access},\n  volume       = {9},\n  pages        = {128494--128505},\n  year         = {2021}\n}\n\n
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\n \n\n \n \n \n \n \n Bayesian Graph Convolutional Neural Networks via Tempered MCMC.\n \n \n \n\n\n \n Chandra, R.; Bhagat, A.; Maharana, M.; and Krivitsky, P. N.\n\n\n \n\n\n\n IEEE Access, 9: 130353–130365. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/access/ChandraBMK21,\n  author       = {Rohitash Chandra and\n                  Ayush Bhagat and\n                  Manavendra Maharana and\n                  Pavel N. Krivitsky},\n  title        = {Bayesian Graph Convolutional Neural Networks via Tempered {MCMC}},\n  journal      = {{IEEE} Access},\n  volume       = {9},\n  pages        = {130353--130365},\n  year         = {2021}\n}\n\n
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\n \n\n \n \n \n \n \n Precipitation reconstruction from climate-sensitive lithologies using Bayesian machine learning.\n \n \n \n\n\n \n Chandra, R.; Cripps, S.; Butterworth, N.; and Müller, R. D.\n\n\n \n\n\n\n Environ. Model. Softw., 139: 105002. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/envsoft/ChandraCBM21,\n  author       = {Rohitash Chandra and\n                  Sally Cripps and\n                  Nathaniel Butterworth and\n                  R. Dietmar M{\\"{u}}ller},\n  title        = {Precipitation reconstruction from climate-sensitive lithologies using\n                  Bayesian machine learning},\n  journal      = {Environ. Model. Softw.},\n  volume       = {139},\n  pages        = {105002},\n  year         = {2021}\n}\n\n
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\n \n\n \n \n \n \n \n Deep learning via LSTM models for COVID-19 infection forecasting in India.\n \n \n \n\n\n \n Chandra, R.; Jain, A.; and Chauhan, D. S.\n\n\n \n\n\n\n CoRR, abs/2101.11881. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2101-11881,\n  author       = {Rohitash Chandra and\n                  Ayush Jain and\n                  Divyanshu Singh Chauhan},\n  title        = {Deep learning via {LSTM} models for {COVID-19} infection forecasting\n                  in India},\n  journal      = {CoRR},\n  volume       = {abs/2101.11881},\n  year         = {2021}\n}\n\n
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\n \n\n \n \n \n \n \n Delhi air quality prediction using LSTM deep learning models with a focus on COVID-19 lockdown.\n \n \n \n\n\n \n Tiwari, A.; Gupta, R.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2102.10551. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2102-10551,\n  author       = {Animesh Tiwari and\n                  Rishabh Gupta and\n                  Rohitash Chandra},\n  title        = {Delhi air quality prediction using {LSTM} deep learning models with\n                  a focus on {COVID-19} lockdown},\n  journal      = {CoRR},\n  volume       = {abs/2102.10551},\n  year         = {2021}\n}\n\n
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\n \n\n \n \n \n \n \n A review of machine learning in processing remote sensing data for mineral exploration.\n \n \n \n\n\n \n Shirmard, H.; Farahbakhsh, E.; Müller, R. D.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2103.07678. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2103-07678,\n  author       = {Hodjat Shirmard and\n                  Ehsan Farahbakhsh and\n                  R. Dietmar M{\\"{u}}ller and\n                  Rohitash Chandra},\n  title        = {A review of machine learning in processing remote sensing data for\n                  mineral exploration},\n  journal      = {CoRR},\n  volume       = {abs/2103.07678},\n  year         = {2021}\n}\n\n
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\n \n\n \n \n \n \n \n Evaluation of deep learning models for multi-step ahead time series prediction.\n \n \n \n\n\n \n Chandra, R.; Goyal, S.; and Gupta, R.\n\n\n \n\n\n\n CoRR, abs/2103.14250. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2103-14250,\n  author       = {Rohitash Chandra and\n                  Shaurya Goyal and\n                  Rishabh Gupta},\n  title        = {Evaluation of deep learning models for multi-step ahead time series\n                  prediction},\n  journal      = {CoRR},\n  volume       = {abs/2103.14250},\n  year         = {2021}\n}\n\n
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\n \n\n \n \n \n \n \n Revisiting Bayesian Autoencoders with MCMC.\n \n \n \n\n\n \n Chandra, R.; Jain, M.; Maharana, M.; and Krivitsky, P. N.\n\n\n \n\n\n\n CoRR, abs/2104.05915. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2104-05915,\n  author       = {Rohitash Chandra and\n                  Mahir Jain and\n                  Manavendra Maharana and\n                  Pavel N. Krivitsky},\n  title        = {Revisiting Bayesian Autoencoders with {MCMC}},\n  journal      = {CoRR},\n  volume       = {abs/2104.05915},\n  year         = {2021}\n}\n\n
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\n \n\n \n \n \n \n \n Memory Capacity of Neural Turing Machines with Matrix Representation.\n \n \n \n\n\n \n Renanse, A.; Chandra, R.; and Sharma, A.\n\n\n \n\n\n\n CoRR, abs/2104.07454. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2104-07454,\n  author       = {Animesh Renanse and\n                  Rohitash Chandra and\n                  Alok Sharma},\n  title        = {Memory Capacity of Neural Turing Machines with Matrix Representation},\n  journal      = {CoRR},\n  volume       = {abs/2104.07454},\n  year         = {2021}\n}\n\n
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\n \n\n \n \n \n \n \n Bayesian graph convolutional neural networks via tempered MCMC.\n \n \n \n\n\n \n Chandra, R.; Bhagat, A.; Maharana, M.; and Krivitsky, P. N.\n\n\n \n\n\n\n CoRR, abs/2104.08438. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2104-08438,\n  author       = {Rohitash Chandra and\n                  Ayush Bhagat and\n                  Manavendra Maharana and\n                  Pavel N. Krivitsky},\n  title        = {Bayesian graph convolutional neural networks via tempered {MCMC}},\n  journal      = {CoRR},\n  volume       = {abs/2104.08438},\n  year         = {2021}\n}\n\n
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\n \n\n \n \n \n \n \n COVID-19 sentiment analysis via deep learning during the rise of novel cases.\n \n \n \n\n\n \n Chandra, R.; and Krishna, A.\n\n\n \n\n\n\n CoRR, abs/2104.10662. 2021.\n \n\n\n\n
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@article{DBLP:journals/corr/abs-2104-10662,\n  author       = {Rohitash Chandra and\n                  Aswin Krishna},\n  title        = {{COVID-19} sentiment analysis via deep learning during the rise of\n                  novel cases},\n  journal      = {CoRR},\n  volume       = {abs/2104.10662},\n  year         = {2021}\n}\n\n
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\n \n\n \n \n \n \n \n SMOTified-GAN for class imbalanced pattern classification problems.\n \n \n \n\n\n \n Sharma, A.; Singh, P. K.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/2108.03235. 2021.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-2108-03235,\n  author       = {Anuraganand Sharma and\n                  Prabhat Kumar Singh and\n                  Rohitash Chandra},\n  title        = {SMOTified-GAN for class imbalanced pattern classification problems},\n  journal      = {CoRR},\n  volume       = {abs/2108.03235},\n  year         = {2021}\n}\n\n
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\n  \n 2020\n \n \n (5)\n \n \n
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\n \n\n \n \n \n \n \n Surrogate-assisted parallel tempering for Bayesian neural learning.\n \n \n \n\n\n \n Chandra, R.; Jain, K.; Kapoor, A.; and Aman, A.\n\n\n \n\n\n\n Eng. Appl. Artif. Intell., 94: 103700. 2020.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/eaai/ChandraJKA20,\n  author       = {Rohitash Chandra and\n                  Konark Jain and\n                  Arpit Kapoor and\n                  Ashray Aman},\n  title        = {Surrogate-assisted parallel tempering for Bayesian neural learning},\n  journal      = {Eng. Appl. Artif. Intell.},\n  volume       = {94},\n  pages        = {103700},\n  year         = {2020}\n}\n\n
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\n \n\n \n \n \n \n \n \\emphBayesreef: A Bayesian inference framework for modelling reef growth in response to environmental change and biological dynamics.\n \n \n \n\n\n \n Pall, J.; Chandra, R.; Azam, D.; Salles, T.; Webster, J. M.; Scalzo, R.; and Cripps, S.\n\n\n \n\n\n\n Environ. Model. Softw., 125: 104610. 2020.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/envsoft/PallCASWSC20,\n  author       = {Jodie Pall and\n                  Rohitash Chandra and\n                  Danial Azam and\n                  Tristan Salles and\n                  Jody M. Webster and\n                  Richard Scalzo and\n                  Sally Cripps},\n  title        = {\\emph{Bayesreef}: {A} Bayesian inference framework for modelling reef\n                  growth in response to environmental change and biological dynamics},\n  journal      = {Environ. Model. Softw.},\n  volume       = {125},\n  pages        = {104610},\n  year         = {2020}\n}\n\n
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\n \n\n \n \n \n \n \n Bayesian neural multi-source transfer learning.\n \n \n \n\n\n \n Chandra, R.; and Kapoor, A.\n\n\n \n\n\n\n Neurocomputing, 378: 54–64. 2020.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/ijon/ChandraK20,\n  author       = {Rohitash Chandra and\n                  Arpit Kapoor},\n  title        = {Bayesian neural multi-source transfer learning},\n  journal      = {Neurocomputing},\n  volume       = {378},\n  pages        = {54--64},\n  year         = {2020}\n}\n\n
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\n \n\n \n \n \n \n \n Integration of Selective Dimensionality Reduction Techniques for Mineral Exploration Using ASTER Satellite Data.\n \n \n \n\n\n \n Shirmard, H.; Farahbakhsh, E.; Pour, A. B.; Muslim, A. M.; Müller, R. D.; and Chandra, R.\n\n\n \n\n\n\n Remote. Sens., 12(8): 1261. 2020.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/remotesensing/ShirmardFPMMC20,\n  author       = {Hodjat Shirmard and\n                  Ehsan Farahbakhsh and\n                  Amin Beiranvand Pour and\n                  Aidy M. Muslim and\n                  R. Dietmar M{\\"{u}}ller and\n                  Rohitash Chandra},\n  title        = {Integration of Selective Dimensionality Reduction Techniques for Mineral\n                  Exploration Using {ASTER} Satellite Data},\n  journal      = {Remote. Sens.},\n  volume       = {12},\n  number       = {8},\n  pages        = {1261},\n  year         = {2020}\n}\n\n
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\n \n\n \n \n \n \n \n 3DWofE: An open-source software package for three-dimensional weights of evidence modeling.\n \n \n \n\n\n \n Farahbakhsh, E.; Hezarkhani, A.; Eslamkish, T.; Bahroudi, A.; and Chandra, R.\n\n\n \n\n\n\n Softw. Impacts, 6: 100039. 2020.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/simpa/FarahbakhshHEBC20,\n  author       = {Ehsan Farahbakhsh and\n                  Ardeshir Hezarkhani and\n                  Taymour Eslamkish and\n                  Abbas Bahroudi and\n                  Rohitash Chandra},\n  title        = {3DWofE: An open-source software package for three-dimensional weights\n                  of evidence modeling},\n  journal      = {Softw. Impacts},\n  volume       = {6},\n  pages        = {100039},\n  year         = {2020}\n}\n\n
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\n  \n 2019\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n Bayeslands: A Bayesian inference approach for parameter uncertainty quantification in Badlands.\n \n \n \n\n\n \n Chandra, R.; Azam, D.; Müller, R. D.; Salles, T.; and Cripps, S.\n\n\n \n\n\n\n Comput. Geosci., 131: 89–101. 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/gandc/ChandraAMSC19,\n  author       = {Rohitash Chandra and\n                  Danial Azam and\n                  R. Dietmar M{\\"{u}}ller and\n                  Tristan Salles and\n                  Sally Cripps},\n  title        = {Bayeslands: {A} Bayesian inference approach for parameter uncertainty\n                  quantification in Badlands},\n  journal      = {Comput. Geosci.},\n  volume       = {131},\n  pages        = {89--101},\n  year         = {2019}\n}\n\n
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\n \n\n \n \n \n \n \n Langevin-gradient parallel tempering for Bayesian neural learning.\n \n \n \n\n\n \n Chandra, R.; Jain, K.; Deo, R. V.; and Cripps, S.\n\n\n \n\n\n\n Neurocomputing, 359: 315–326. 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/ijon/ChandraJDC19,\n  author       = {Rohitash Chandra and\n                  Konark Jain and\n                  Ratneel Vikash Deo and\n                  Sally Cripps},\n  title        = {Langevin-gradient parallel tempering for Bayesian neural learning},\n  journal      = {Neurocomputing},\n  volume       = {359},\n  pages        = {315--326},\n  year         = {2019}\n}\n\n
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\n \n\n \n \n \n \n \n Multi-step-ahead Cyclone Intensity Prediction with Bayesian Neural Networks.\n \n \n \n\n\n \n Deo, R.; and Chandra, R.\n\n\n \n\n\n\n In PRICAI (2), volume 11671, of Lecture Notes in Computer Science, pages 282–295, 2019. Springer\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/pricai/DeoC19,\n  author       = {Ratneel Deo and\n                  Rohitash Chandra},\n  title        = {Multi-step-ahead Cyclone Intensity Prediction with Bayesian Neural\n                  Networks},\n  booktitle    = {{PRICAI} {(2)}},\n  series       = {Lecture Notes in Computer Science},\n  volume       = {11671},\n  pages        = {282--295},\n  publisher    = {Springer},\n  year         = {2019}\n}\n\n
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\n  \n 2018\n \n \n (15)\n \n \n
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\n \n\n \n \n \n \n \n Co-evolutionary multi-task learning for dynamic time series prediction.\n \n \n \n\n\n \n Chandra, R.; Ong, Y.; and Goh, C.\n\n\n \n\n\n\n Appl. Soft Comput., 70: 576–589. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/asc/ChandraOG18,\n  author       = {Rohitash Chandra and\n                  Yew{-}Soon Ong and\n                  Chi{-}Keong Goh},\n  title        = {Co-evolutionary multi-task learning for dynamic time series prediction},\n  journal      = {Appl. Soft Comput.},\n  volume       = {70},\n  pages        = {576--589},\n  year         = {2018}\n}\n\n
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\n \n\n \n \n \n \n \n Coevolutionary multi-task learning for feature-based modular pattern classification.\n \n \n \n\n\n \n Chandra, R.; and Cripps, S.\n\n\n \n\n\n\n Neurocomputing, 319: 164–175. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/ijon/ChandraC18,\n  author       = {Rohitash Chandra and\n                  Sally Cripps},\n  title        = {Coevolutionary multi-task learning for feature-based modular pattern\n                  classification},\n  journal      = {Neurocomputing},\n  volume       = {319},\n  pages        = {164--175},\n  year         = {2018}\n}\n\n
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\n \n\n \n \n \n \n \n Evolutionary Multi-task Learning for Modular Knowledge Representation in Neural Networks.\n \n \n \n\n\n \n Chandra, R.; Gupta, A.; Ong, Y.; and Goh, C.\n\n\n \n\n\n\n Neural Process. Lett., 47(3): 993–1009. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/npl/ChandraGOG18,\n  author       = {Rohitash Chandra and\n                  Abhishek Gupta and\n                  Yew{-}Soon Ong and\n                  Chi{-}Keong Goh},\n  title        = {Evolutionary Multi-task Learning for Modular Knowledge Representation\n                  in Neural Networks},\n  journal      = {Neural Process. Lett.},\n  volume       = {47},\n  number       = {3},\n  pages        = {993--1009},\n  year         = {2018}\n}\n\n
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\n \n\n \n \n \n \n \n Multi-Task Modular Backpropagation For Dynamic Time Series Prediction.\n \n \n \n\n\n \n Chandra, R.\n\n\n \n\n\n\n In IJCNN, pages 1–7, 2018. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/ijcnn/Chandra18,\n  author       = {Rohitash Chandra},\n  title        = {Multi-Task Modular Backpropagation For Dynamic Time Series Prediction},\n  booktitle    = {{IJCNN}},\n  pages        = {1--7},\n  publisher    = {{IEEE}},\n  year         = {2018}\n}\n\n
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\n \n\n \n \n \n \n \n Bayesian Multi-task Learning for Dynamic Time Series Prediction.\n \n \n \n\n\n \n Chandra, R.; and Cripps, S.\n\n\n \n\n\n\n In IJCNN, pages 1–8, 2018. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/ijcnn/ChandraC18,\n  author       = {Rohitash Chandra and\n                  Sally Cripps},\n  title        = {Bayesian Multi-task Learning for Dynamic Time Series Prediction},\n  booktitle    = {{IJCNN}},\n  pages        = {1--8},\n  publisher    = {{IEEE}},\n  year         = {2018}\n}\n\n
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\n \n\n \n \n \n \n \n Information Collection Strategies In Memetic Cooperative Neuroevolution For Time Series Prediction.\n \n \n \n\n\n \n Wong, G.; Sharma, A.; and Chandra, R.\n\n\n \n\n\n\n In IJCNN, pages 1–6, 2018. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/ijcnn/WongSC18,\n  author       = {Gary Wong and\n                  Anuraganand Sharma and\n                  Rohitash Chandra},\n  title        = {Information Collection Strategies In Memetic Cooperative Neuroevolution\n                  For Time Series Prediction},\n  booktitle    = {{IJCNN}},\n  pages        = {1--6},\n  publisher    = {{IEEE}},\n  year         = {2018}\n}\n\n
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\n \n\n \n \n \n \n \n Cyclone Track Prediction with Matrix Neural Networks.\n \n \n \n\n\n \n Zhang, Y.; Chandra, R.; and Gao, J.\n\n\n \n\n\n\n In IJCNN, pages 1–8, 2018. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/ijcnn/ZhangCG18,\n  author       = {Yanfei Zhang and\n                  Rohitash Chandra and\n                  Junbin Gao},\n  title        = {Cyclone Track Prediction with Matrix Neural Networks},\n  booktitle    = {{IJCNN}},\n  pages        = {1--8},\n  publisher    = {{IEEE}},\n  year         = {2018}\n}\n\n
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\n \n\n \n \n \n \n \n BayesLands: A Bayesian inference approach for parameter uncertainty quantification in Badlands.\n \n \n \n\n\n \n Chandra, R.; Azam, D.; Müller, R. D.; Salles, T.; and Cripps, S.\n\n\n \n\n\n\n CoRR, abs/1805.03696. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-1805-03696,\n  author       = {Rohitash Chandra and\n                  Danial Azam and\n                  R. Dietmar M{\\"{u}}ller and\n                  Tristan Salles and\n                  Sally Cripps},\n  title        = {BayesLands: {A} Bayesian inference approach for parameter uncertainty\n                  quantification in Badlands},\n  journal      = {CoRR},\n  volume       = {abs/1805.03696},\n  year         = {2018}\n}\n\n
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\n \n\n \n \n \n \n \n Multi-core parallel tempering Bayeslands for basin and landscape evolution.\n \n \n \n\n\n \n Chandra, R.; Müller, R. D.; Deo, R.; Butterworth, N.; Salles, T.; and Cripps, S.\n\n\n \n\n\n\n CoRR, abs/1806.10939. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-1806-10939,\n  author       = {Rohitash Chandra and\n                  R. Dietmar M{\\"{u}}ller and\n                  Ratneel Deo and\n                  Nathaniel Butterworth and\n                  Tristan Salles and\n                  Sally Cripps},\n  title        = {Multi-core parallel tempering Bayeslands for basin and landscape evolution},\n  journal      = {CoRR},\n  volume       = {abs/1806.10939},\n  year         = {2018}\n}\n\n
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\n \n\n \n \n \n \n \n BayesReef: A Bayesian inference framework for modelling reef growth in response to environmental change and biological dynamics.\n \n \n \n\n\n \n Pall, J.; Chandra, R.; Azam, D.; Salles, T.; Webster, J. M.; and Cripps, S.\n\n\n \n\n\n\n CoRR, abs/1808.02763. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-1808-02763,\n  author       = {Jodie Pall and\n                  Rohitash Chandra and\n                  Danial Azam and\n                  Tristan Salles and\n                  Jody M. Webster and\n                  Sally Cripps},\n  title        = {BayesReef: {A} Bayesian inference framework for modelling reef growth\n                  in response to environmental change and biological dynamics},\n  journal      = {CoRR},\n  volume       = {abs/1808.02763},\n  year         = {2018}\n}\n\n
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\n \n\n \n \n \n \n \n Computer vision-based framework for extracting geological lineaments from optical remote sensing data.\n \n \n \n\n\n \n Farahbakhsh, E.; Chandra, R.; Olierook, H. K. H.; Scalzo, R.; Clark, C.; Reddy, S. M.; and Müller, R. D.\n\n\n \n\n\n\n CoRR, abs/1810.02320. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-1810-02320,\n  author       = {Ehsan Farahbakhsh and\n                  Rohitash Chandra and\n                  Hugo K. H. Olierook and\n                  Richard Scalzo and\n                  Chris Clark and\n                  Steven M. Reddy and\n                  R. Dietmar M{\\"{u}}ller},\n  title        = {Computer vision-based framework for extracting geological lineaments\n                  from optical remote sensing data},\n  journal      = {CoRR},\n  volume       = {abs/1810.02320},\n  year         = {2018}\n}\n\n
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\n \n\n \n \n \n \n \n Langevin-gradient parallel tempering for Bayesian neural learning.\n \n \n \n\n\n \n Chandra, R.; Jain, K.; Deo, R. V.; and Cripps, S.\n\n\n \n\n\n\n CoRR, abs/1811.04343. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-1811-04343,\n  author       = {Rohitash Chandra and\n                  Konark Jain and\n                  Ratneel Vikash Deo and\n                  Sally Cripps},\n  title        = {Langevin-gradient parallel tempering for Bayesian neural learning},\n  journal      = {CoRR},\n  volume       = {abs/1811.04343},\n  year         = {2018}\n}\n\n
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\n \n\n \n \n \n \n \n Surrogate-assisted parallel tempering for Bayesian neural learning.\n \n \n \n\n\n \n Chandra, R.; Jain, K.; and Kapoor, A.\n\n\n \n\n\n\n CoRR, abs/1811.08687. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-1811-08687,\n  author       = {Rohitash Chandra and\n                  Konark Jain and\n                  Arpit Kapoor},\n  title        = {Surrogate-assisted parallel tempering for Bayesian neural learning},\n  journal      = {CoRR},\n  volume       = {abs/1811.08687},\n  year         = {2018}\n}\n\n
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\n \n\n \n \n \n \n \n Efficiency and robustness in Monte Carlo sampling of 3-D geophysical inversions with Obsidian v0.1.2: Setting up for success.\n \n \n \n\n\n \n Scalzo, R.; Kohn, D.; Olierook, H. K. H.; Houseman, G.; Chandra, R.; Girolami, M. A.; and Cripps, S.\n\n\n \n\n\n\n CoRR, abs/1812.00318. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-1812-00318,\n  author       = {Richard Scalzo and\n                  David Kohn and\n                  Hugo K. H. Olierook and\n                  Gregory Houseman and\n                  Rohitash Chandra and\n                  Mark A. Girolami and\n                  Sally Cripps},\n  title        = {Efficiency and robustness in Monte Carlo sampling of 3-D geophysical\n                  inversions with Obsidian v0.1.2: Setting up for success},\n  journal      = {CoRR},\n  volume       = {abs/1812.00318},\n  year         = {2018}\n}\n\n
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\n \n\n \n \n \n \n \n Surrogate-assisted Bayesian inversion for landscape and basin evolution models.\n \n \n \n\n\n \n Chandra, R.; Azam, D.; Kapoor, A.; and Müller, R. D.\n\n\n \n\n\n\n CoRR, abs/1812.08655. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-1812-08655,\n  author       = {Rohitash Chandra and\n                  Danial Azam and\n                  Arpit Kapoor and\n                  R. Dietmar M{\\"{u}}ller},\n  title        = {Surrogate-assisted Bayesian inversion for landscape and basin evolution\n                  models},\n  journal      = {CoRR},\n  volume       = {abs/1812.08655},\n  year         = {2018}\n}\n\n
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\n  \n 2017\n \n \n (11)\n \n \n
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\n \n\n \n \n \n \n \n Face detection and recognition in an unconstrained environment for mobile visual assistive system.\n \n \n \n\n\n \n Chaudhry, S.; and Chandra, R.\n\n\n \n\n\n\n Appl. Soft Comput., 53: 168–180. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/asc/ChaudhryC17,\n  author       = {Shonal Chaudhry and\n                  Rohitash Chandra},\n  title        = {Face detection and recognition in an unconstrained environment for\n                  mobile visual assistive system},\n  journal      = {Appl. Soft Comput.},\n  volume       = {53},\n  pages        = {168--180},\n  year         = {2017}\n}\n\n
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\n \n\n \n \n \n \n \n Co-evolutionary multi-task learning with predictive recurrence for multi-step chaotic time series prediction.\n \n \n \n\n\n \n Chandra, R.; Ong, Y.; and Goh, C.\n\n\n \n\n\n\n Neurocomputing, 243: 21–34. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/ijon/ChandraOG17,\n  author       = {Rohitash Chandra and\n                  Yew{-}Soon Ong and\n                  Chi{-}Keong Goh},\n  title        = {Co-evolutionary multi-task learning with predictive recurrence for\n                  multi-step chaotic time series prediction},\n  journal      = {Neurocomputing},\n  volume       = {243},\n  pages        = {21--34},\n  year         = {2017}\n}\n\n
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\n \n\n \n \n \n \n \n Multi-task Modular Backpropagation for Feature-Based Pattern Classification.\n \n \n \n\n\n \n Chandra, R.\n\n\n \n\n\n\n In ICONIP (6), volume 10639, of Lecture Notes in Computer Science, pages 558–566, 2017. Springer\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/iconip/Chandra17b,\n  author       = {Rohitash Chandra},\n  title        = {Multi-task Modular Backpropagation for Feature-Based Pattern Classification},\n  booktitle    = {{ICONIP} {(6)}},\n  series       = {Lecture Notes in Computer Science},\n  volume       = {10639},\n  pages        = {558--566},\n  publisher    = {Springer},\n  year         = {2017}\n}\n\n
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\n \n\n \n \n \n \n \n Bayesian Neural Learning via Langevin Dynamics for Chaotic Time Series Prediction.\n \n \n \n\n\n \n Chandra, R.; Azizi, L.; and Cripps, S.\n\n\n \n\n\n\n In ICONIP (5), volume 10638, of Lecture Notes in Computer Science, pages 564–573, 2017. Springer\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/iconip/ChandraAC17,\n  author       = {Rohitash Chandra and\n                  Lamiae Azizi and\n                  Sally Cripps},\n  title        = {Bayesian Neural Learning via Langevin Dynamics for Chaotic Time Series\n                  Prediction},\n  booktitle    = {{ICONIP} {(5)}},\n  series       = {Lecture Notes in Computer Science},\n  volume       = {10638},\n  pages        = {564--573},\n  publisher    = {Springer},\n  year         = {2017}\n}\n\n
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\n \n\n \n \n \n \n \n Dynamic Cyclone Wind-Intensity Prediction Using Co-Evolutionary Multi-task Learning.\n \n \n \n\n\n \n Chandra, R.\n\n\n \n\n\n\n In ICONIP (5), volume 10638, of Lecture Notes in Computer Science, pages 618–627, 2017. Springer\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/iconip/Chandra17,\n  author       = {Rohitash Chandra},\n  title        = {Dynamic Cyclone Wind-Intensity Prediction Using Co-Evolutionary Multi-task\n                  Learning},\n  booktitle    = {{ICONIP} {(5)}},\n  series       = {Lecture Notes in Computer Science},\n  volume       = {10638},\n  pages        = {618--627},\n  publisher    = {Springer},\n  year         = {2017}\n}\n\n
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\n \n\n \n \n \n \n \n Co-evolutionary Multi-task Learning for Modular Pattern Classification.\n \n \n \n\n\n \n Chandra, R.\n\n\n \n\n\n\n In ICONIP (6), volume 10639, of Lecture Notes in Computer Science, pages 692–701, 2017. Springer\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/iconip/Chandra17c,\n  author       = {Rohitash Chandra},\n  title        = {Co-evolutionary Multi-task Learning for Modular Pattern Classification},\n  booktitle    = {{ICONIP} {(6)}},\n  series       = {Lecture Notes in Computer Science},\n  volume       = {10639},\n  pages        = {692--701},\n  publisher    = {Springer},\n  year         = {2017}\n}\n\n
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\n \n\n \n \n \n \n \n Towards an Affective Computational Model for Machine Consciousness.\n \n \n \n\n\n \n Chandra, R.\n\n\n \n\n\n\n In ICONIP (5), volume 10638, of Lecture Notes in Computer Science, pages 897–907, 2017. Springer\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/iconip/Chandra17a,\n  author       = {Rohitash Chandra},\n  title        = {Towards an Affective Computational Model for Machine Consciousness},\n  booktitle    = {{ICONIP} {(5)}},\n  series       = {Lecture Notes in Computer Science},\n  volume       = {10638},\n  pages        = {897--907},\n  publisher    = {Springer},\n  year         = {2017}\n}\n\n
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\n \n\n \n \n \n \n \n An affective computational model for machine consciousness.\n \n \n \n\n\n \n Chandra, R.\n\n\n \n\n\n\n CoRR, abs/1701.00349. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/Chandra17,\n  author       = {Rohitash Chandra},\n  title        = {An affective computational model for machine consciousness},\n  journal      = {CoRR},\n  volume       = {abs/1701.00349},\n  year         = {2017}\n}\n\n
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\n \n\n \n \n \n \n \n Towards prediction of rapid intensification in tropical cyclones with recurrent neural networks.\n \n \n \n\n\n \n Chandra, R.\n\n\n \n\n\n\n CoRR, abs/1701.04518. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/Chandra17a,\n  author       = {Rohitash Chandra},\n  title        = {Towards prediction of rapid intensification in tropical cyclones with\n                  recurrent neural networks},\n  journal      = {CoRR},\n  volume       = {abs/1701.04518},\n  year         = {2017}\n}\n\n
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\n \n\n \n \n \n \n \n Co-evolutionary multi-task learning for dynamic time series prediction.\n \n \n \n\n\n \n Chandra, R.; Ong, Y.; and Goh, C.\n\n\n \n\n\n\n CoRR, abs/1703.01887. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/ChandraOG17,\n  author       = {Rohitash Chandra and\n                  Yew{-}Soon Ong and\n                  Chi{-}Keong Goh},\n  title        = {Co-evolutionary multi-task learning for dynamic time series prediction},\n  journal      = {CoRR},\n  volume       = {abs/1703.01887},\n  year         = {2017}\n}\n\n
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\n \n\n \n \n \n \n \n Stacked transfer learning for tropical cyclone intensity prediction.\n \n \n \n\n\n \n Deo, R. V.; Chandra, R.; and Sharma, A.\n\n\n \n\n\n\n CoRR, abs/1708.06539. 2017.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/abs-1708-06539,\n  author       = {Ratneel Vikash Deo and\n                  Rohitash Chandra and\n                  Anuraganand Sharma},\n  title        = {Stacked transfer learning for tropical cyclone intensity prediction},\n  journal      = {CoRR},\n  volume       = {abs/1708.06539},\n  year         = {2017}\n}\n\n
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\n  \n 2016\n \n \n (15)\n \n \n
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\n \n\n \n \n \n \n \n Evaluation of co-evolutionary neural network architectures for time series prediction with mobile application in finance.\n \n \n \n\n\n \n Chandra, R.; and Chand, S.\n\n\n \n\n\n\n Appl. Soft Comput., 49: 462–473. 2016.\n \n\n\n\n
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@article{DBLP:journals/asc/ChandraC16,\n  author       = {Rohitash Chandra and\n                  Shelvin Chand},\n  title        = {Evaluation of co-evolutionary neural network architectures for time\n                  series prediction with mobile application in finance},\n  journal      = {Appl. Soft Comput.},\n  volume       = {49},\n  pages        = {462--473},\n  year         = {2016}\n}\n\n
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\n \n\n \n \n \n \n \n The forward kinematics of the 6-6 parallel manipulator using an evolutionary algorithm based on generalized generation gap with parent-centric crossover.\n \n \n \n\n\n \n Rolland, L.; and Chandra, R.\n\n\n \n\n\n\n Robotica, 34(1): 1–22. 2016.\n \n\n\n\n
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@article{DBLP:journals/robotica/RollandC16,\n  author       = {Luc Rolland and\n                  Rohitash Chandra},\n  title        = {The forward kinematics of the 6-6 parallel manipulator using an evolutionary\n                  algorithm based on generalized generation gap with parent-centric\n                  crossover},\n  journal      = {Robotica},\n  volume       = {34},\n  number       = {1},\n  pages        = {1--22},\n  year         = {2016}\n}\n\n
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\n \n\n \n \n \n \n \n Competitive Island Cooperative Neuro-evolution of Feedforward Networks for Time Series Prediction.\n \n \n \n\n\n \n Nand, R.; and Chandra, R.\n\n\n \n\n\n\n In ACALCI, volume 9592, of Lecture Notes in Computer Science, pages 160–170, 2016. Springer\n \n\n\n\n
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@inproceedings{DBLP:conf/acal/NandC16,\n  author       = {Ravneil Nand and\n                  Rohitash Chandra},\n  title        = {Competitive Island Cooperative Neuro-evolution of Feedforward Networks\n                  for Time Series Prediction},\n  booktitle    = {{ACALCI}},\n  series       = {Lecture Notes in Computer Science},\n  volume       = {9592},\n  pages        = {160--170},\n  publisher    = {Springer},\n  year         = {2016}\n}\n\n
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\n \n\n \n \n \n \n \n Reverse Neuron Level Decomposition for Cooperative Neuro-Evolution of Feedforward Networks for Time Series Prediction.\n \n \n \n\n\n \n Nand, R.; and Chandra, R.\n\n\n \n\n\n\n In ACALCI, volume 9592, of Lecture Notes in Computer Science, pages 171–182, 2016. Springer\n \n\n\n\n
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@inproceedings{DBLP:conf/acal/NandC16a,\n  author       = {Ravneil Nand and\n                  Rohitash Chandra},\n  title        = {Reverse Neuron Level Decomposition for Cooperative Neuro-Evolution\n                  of Feedforward Networks for Time Series Prediction},\n  booktitle    = {{ACALCI}},\n  series       = {Lecture Notes in Computer Science},\n  volume       = {9592},\n  pages        = {171--182},\n  publisher    = {Springer},\n  year         = {2016}\n}\n\n
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\n \n\n \n \n \n \n \n Coevolutionary Feature Selection and Reconstruction in Neuro-Evolution for Time Series Prediction.\n \n \n \n\n\n \n Nand, R.; and Chandra, R.\n\n\n \n\n\n\n In ACALCI, volume 9592, of Lecture Notes in Computer Science, pages 285–297, 2016. Springer\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/acal/NandC16b,\n  author       = {Ravneil Nand and\n                  Rohitash Chandra},\n  title        = {Coevolutionary Feature Selection and Reconstruction in Neuro-Evolution\n                  for Time Series Prediction},\n  booktitle    = {{ACALCI}},\n  series       = {Lecture Notes in Computer Science},\n  volume       = {9592},\n  pages        = {285--297},\n  publisher    = {Springer},\n  year         = {2016}\n}\n\n
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\n \n\n \n \n \n \n \n Contribution based multi-island competitive cooperative coevolution.\n \n \n \n\n\n \n Bali, K.; Chandra, R.; and Omidvar, M. N.\n\n\n \n\n\n\n In CEC, pages 1823–1830, 2016. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/cec/BaliCO16,\n  author       = {Kavitesh Bali and\n                  Rohitash Chandra and\n                  Mohammad Nabi Omidvar},\n  title        = {Contribution based multi-island competitive cooperative coevolution},\n  booktitle    = {{CEC}},\n  pages        = {1823--1830},\n  publisher    = {{IEEE}},\n  year         = {2016}\n}\n\n
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\n \n\n \n \n \n \n \n Multi-step-ahead chaotic time series prediction using coevolutionary recurrent neural networks.\n \n \n \n\n\n \n Hussein, S.; Chandra, R.; and Sharma, A.\n\n\n \n\n\n\n In CEC, pages 3084–3091, 2016. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/cec/HusseinCS16,\n  author       = {Shamina Hussein and\n                  Rohitash Chandra and\n                  Anuraganand Sharma},\n  title        = {Multi-step-ahead chaotic time series prediction using coevolutionary\n                  recurrent neural networks},\n  booktitle    = {{CEC}},\n  pages        = {3084--3091},\n  publisher    = {{IEEE}},\n  year         = {2016}\n}\n\n
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\n \n\n \n \n \n \n \n Cooperative neuro-evolutionary recurrent neural networks for solar power prediction.\n \n \n \n\n\n \n Rana, M.; Chandra, R.; and Agelidis, V. G.\n\n\n \n\n\n\n In CEC, pages 4691–4698, 2016. IEEE\n \n\n\n\n
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@inproceedings{DBLP:conf/cec/RanaCA16,\n  author       = {Mashud Rana and\n                  Rohitash Chandra and\n                  Vassilios G. Agelidis},\n  title        = {Cooperative neuro-evolutionary recurrent neural networks for solar\n                  power prediction},\n  booktitle    = {{CEC}},\n  pages        = {4691--4698},\n  publisher    = {{IEEE}},\n  year         = {2016}\n}\n\n
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\n \n\n \n \n \n \n \n On the relationship of degree of separability with depth of evolution in decomposition for cooperative coevolution.\n \n \n \n\n\n \n Chandra, R.; Deo, R.; Bali, K.; and Sharma, A.\n\n\n \n\n\n\n In CEC, pages 4823–4830, 2016. IEEE\n \n\n\n\n
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@inproceedings{DBLP:conf/cec/ChandraDBS16,\n  author       = {Rohitash Chandra and\n                  Ratneel Deo and\n                  Kavitesh Bali and\n                  Anurag Sharma},\n  title        = {On the relationship of degree of separability with depth of evolution\n                  in decomposition for cooperative coevolution},\n  booktitle    = {{CEC}},\n  pages        = {4823--4830},\n  publisher    = {{IEEE}},\n  year         = {2016}\n}\n\n
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\n \n\n \n \n \n \n \n Chaotic Feature Selection and Reconstruction in Time Series Prediction.\n \n \n \n\n\n \n Hussein, S.; and Chandra, R.\n\n\n \n\n\n\n In ICONIP (3), volume 9949, of Lecture Notes in Computer Science, pages 3–11, 2016. \n \n\n\n\n
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@inproceedings{DBLP:conf/iconip/HusseinC16,\n  author       = {Shamina Hussein and\n                  Rohitash Chandra},\n  title        = {Chaotic Feature Selection and Reconstruction in Time Series Prediction},\n  booktitle    = {{ICONIP} {(3)}},\n  series       = {Lecture Notes in Computer Science},\n  volume       = {9949},\n  pages        = {3--11},\n  year         = {2016}\n}\n\n
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\n \n\n \n \n \n \n \n Evolutionary Multi-task Learning for Modular Training of Feedforward Neural Networks.\n \n \n \n\n\n \n Chandra, R.; Gupta, A.; Ong, Y.; and Goh, C. K.\n\n\n \n\n\n\n In ICONIP (2), volume 9948, of Lecture Notes in Computer Science, pages 37–46, 2016. \n \n\n\n\n
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@inproceedings{DBLP:conf/iconip/ChandraGOG16,\n  author       = {Rohitash Chandra and\n                  Abhishek Gupta and\n                  Yew{-}Soon Ong and\n                  Chi Keong Goh},\n  title        = {Evolutionary Multi-task Learning for Modular Training of Feedforward\n                  Neural Networks},\n  booktitle    = {{ICONIP} {(2)}},\n  series       = {Lecture Notes in Computer Science},\n  volume       = {9948},\n  pages        = {37--46},\n  year         = {2016}\n}\n\n
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\n \n\n \n \n \n \n \n Memetic Cooperative Neuro-Evolution for Chaotic Time Series Prediction.\n \n \n \n\n\n \n Wong, G.; Chandra, R.; and Sharma, A.\n\n\n \n\n\n\n In ICONIP (3), volume 9949, of Lecture Notes in Computer Science, pages 299–308, 2016. \n \n\n\n\n
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@inproceedings{DBLP:conf/iconip/WongCS16,\n  author       = {Gary Wong and\n                  Rohitash Chandra and\n                  Anuraganand Sharma},\n  title        = {Memetic Cooperative Neuro-Evolution for Chaotic Time Series Prediction},\n  booktitle    = {{ICONIP} {(3)}},\n  series       = {Lecture Notes in Computer Science},\n  volume       = {9949},\n  pages        = {299--308},\n  year         = {2016}\n}\n\n
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\n \n\n \n \n \n \n \n Unconstrained Face Detection from a Mobile Source Using Convolutional Neural Networks.\n \n \n \n\n\n \n Chaudhry, S.; and Chandra, R.\n\n\n \n\n\n\n In ICONIP (2), volume 9948, of Lecture Notes in Computer Science, pages 567–576, 2016. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/iconip/ChaudhryC16,\n  author       = {Shonal Chaudhry and\n                  Rohitash Chandra},\n  title        = {Unconstrained Face Detection from a Mobile Source Using Convolutional\n                  Neural Networks},\n  booktitle    = {{ICONIP} {(2)}},\n  series       = {Lecture Notes in Computer Science},\n  volume       = {9948},\n  pages        = {567--576},\n  year         = {2016}\n}\n\n
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\n \n\n \n \n \n \n \n Identification of minimal timespan problem for recurrent neural networks with application to cyclone wind-intensity prediction.\n \n \n \n\n\n \n Deo, R.; and Chandra, R.\n\n\n \n\n\n\n In IJCNN, pages 489–496, 2016. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/ijcnn/DeoC16,\n  author       = {Ratneel Deo and\n                  Rohitash Chandra},\n  title        = {Identification of minimal timespan problem for recurrent neural networks\n                  with application to cyclone wind-intensity prediction},\n  booktitle    = {{IJCNN}},\n  pages        = {489--496},\n  publisher    = {{IEEE}},\n  year         = {2016}\n}\n\n
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\n \n\n \n \n \n \n \n An architecture for encoding two-dimensional cyclone track prediction problem in coevolutionary recurrent neural networks.\n \n \n \n\n\n \n Chandra, R.; Deo, R.; and Omlin, C. W.\n\n\n \n\n\n\n In IJCNN, pages 4865–4872, 2016. IEEE\n \n\n\n\n
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@inproceedings{DBLP:conf/ijcnn/ChandraDO16,\n  author       = {Rohitash Chandra and\n                  Ratneel Deo and\n                  Christian W. Omlin},\n  title        = {An architecture for encoding two-dimensional cyclone track prediction\n                  problem in coevolutionary recurrent neural networks},\n  booktitle    = {{IJCNN}},\n  pages        = {4865--4872},\n  publisher    = {{IEEE}},\n  year         = {2016}\n}\n\n
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\n \n\n \n \n \n \n \n Global-local population memetic algorithm for solving the forward kinematics of parallel manipulators.\n \n \n \n\n\n \n Chandra, R.; and Rolland, L.\n\n\n \n\n\n\n Connect. Sci., 27(1): 22–39. 2015.\n \n\n\n\n
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@article{DBLP:journals/connection/ChandraR15,\n  author       = {Rohitash Chandra and\n                  Luc Rolland},\n  title        = {Global-local population memetic algorithm for solving the forward\n                  kinematics of parallel manipulators},\n  journal      = {Connect. Sci.},\n  volume       = {27},\n  number       = {1},\n  pages        = {22--39},\n  year         = {2015}\n}\n\n
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\n \n\n \n \n \n \n \n Competition and Collaboration in Cooperative Coevolution of Elman Recurrent Neural Networks for Time-Series Prediction.\n \n \n \n\n\n \n Chandra, R.\n\n\n \n\n\n\n IEEE Trans. Neural Networks Learn. Syst., 26(12): 3123–3136. 2015.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/tnn/Chandra15,\n  author       = {Rohitash Chandra},\n  title        = {Competition and Collaboration in Cooperative Coevolution of Elman\n                  Recurrent Neural Networks for Time-Series Prediction},\n  journal      = {{IEEE} Trans. Neural Networks Learn. Syst.},\n  volume       = {26},\n  number       = {12},\n  pages        = {3123--3136},\n  year         = {2015}\n}\n\n
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\n \n\n \n \n \n \n \n Scaling up Multi-island Competitive Cooperative Coevolution for Real Parameter Global Optimisation.\n \n \n \n\n\n \n Bali, K. K.; and Chandra, R.\n\n\n \n\n\n\n In Australasian Conference on Artificial Intelligence, volume 9457, of Lecture Notes in Computer Science, pages 34–48, 2015. Springer\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/ausai/BaliC15,\n  author       = {Kavitesh K. Bali and\n                  Rohitash Chandra},\n  title        = {Scaling up Multi-island Competitive Cooperative Coevolution for Real\n                  Parameter Global Optimisation},\n  booktitle    = {Australasian Conference on Artificial Intelligence},\n  series       = {Lecture Notes in Computer Science},\n  volume       = {9457},\n  pages        = {34--48},\n  publisher    = {Springer},\n  year         = {2015}\n}\n\n
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\n \n\n \n \n \n \n \n Competitive two-island cooperative coevolution for real parameter global optimisation.\n \n \n \n\n\n \n Chandra, R.; and Bali, K.\n\n\n \n\n\n\n In CEC, pages 93–100, 2015. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/cec/ChandraB15,\n  author       = {Rohitash Chandra and\n                  Kavitesh Bali},\n  title        = {Competitive two-island cooperative coevolution for real parameter\n                  global optimisation},\n  booktitle    = {{CEC}},\n  pages        = {93--100},\n  publisher    = {{IEEE}},\n  year         = {2015}\n}\n\n
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\n \n\n \n \n \n \n \n Multi-objective cooperative neuro-evolution of recurrent neural networks for time series prediction.\n \n \n \n\n\n \n Chandra, R.\n\n\n \n\n\n\n In CEC, pages 101–108, 2015. IEEE\n \n\n\n\n
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@inproceedings{DBLP:conf/cec/Chandra15,\n  author       = {Rohitash Chandra},\n  title        = {Multi-objective cooperative neuro-evolution of recurrent neural networks\n                  for time series prediction},\n  booktitle    = {{CEC}},\n  pages        = {101--108},\n  publisher    = {{IEEE}},\n  year         = {2015}\n}\n\n
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\n \n\n \n \n \n \n \n Cooperative neuro-evolution of Elman recurrent networks for tropical cyclone wind-intensity prediction in the South Pacific region.\n \n \n \n\n\n \n Chandra, R.; and Dayal, K.\n\n\n \n\n\n\n In CEC, pages 1784–1791, 2015. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/cec/ChandraD15,\n  author       = {Rohitash Chandra and\n                  Kavina Dayal},\n  title        = {Cooperative neuro-evolution of Elman recurrent networks for tropical\n                  cyclone wind-intensity prediction in the South Pacific region},\n  booktitle    = {{CEC}},\n  pages        = {1784--1791},\n  publisher    = {{IEEE}},\n  year         = {2015}\n}\n\n
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\n \n\n \n \n \n \n \n Coevolutionary Recurrent Neural Networks for Prediction of Rapid Intensification in Wind Intensity of Tropical Cyclones in the South Pacific Region.\n \n \n \n\n\n \n Chandra, R.; and Dayal, K. S.\n\n\n \n\n\n\n In ICONIP (3), volume 9491, of Lecture Notes in Computer Science, pages 43–52, 2015. Springer\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/iconip/ChandraD15,\n  author       = {Rohitash Chandra and\n                  Kavina S. Dayal},\n  title        = {Coevolutionary Recurrent Neural Networks for Prediction of Rapid Intensification\n                  in Wind Intensity of Tropical Cyclones in the South Pacific Region},\n  booktitle    = {{ICONIP} {(3)}},\n  series       = {Lecture Notes in Computer Science},\n  volume       = {9491},\n  pages        = {43--52},\n  publisher    = {Springer},\n  year         = {2015}\n}\n\n
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\n \n\n \n \n \n \n \n Neuron-Synapse Level Problem Decomposition Method for Cooperative Neuro-Evolution of Feedforward Networks for Time Series Prediction.\n \n \n \n\n\n \n Nand, R.; and Chandra, R.\n\n\n \n\n\n\n In ICONIP (3), volume 9491, of Lecture Notes in Computer Science, pages 90–100, 2015. Springer\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/iconip/NandC15,\n  author       = {Ravneil Nand and\n                  Rohitash Chandra},\n  title        = {Neuron-Synapse Level Problem Decomposition Method for Cooperative\n                  Neuro-Evolution of Feedforward Networks for Time Series Prediction},\n  booktitle    = {{ICONIP} {(3)}},\n  series       = {Lecture Notes in Computer Science},\n  volume       = {9491},\n  pages        = {90--100},\n  publisher    = {Springer},\n  year         = {2015}\n}\n\n
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\n \n\n \n \n \n \n \n Multi-Island Competitive Cooperative Coevolution for Real Parameter Global Optimization.\n \n \n \n\n\n \n Bali, K. K.; and Chandra, R.\n\n\n \n\n\n\n In ICONIP (3), volume 9491, of Lecture Notes in Computer Science, pages 127–136, 2015. Springer\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/iconip/BaliC15,\n  author       = {Kavitesh K. Bali and\n                  Rohitash Chandra},\n  title        = {Multi-Island Competitive Cooperative Coevolution for Real Parameter\n                  Global Optimization},\n  booktitle    = {{ICONIP} {(3)}},\n  series       = {Lecture Notes in Computer Science},\n  volume       = {9491},\n  pages        = {127--136},\n  publisher    = {Springer},\n  year         = {2015}\n}\n\n
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\n \n\n \n \n \n \n \n Competitive Island-Based Cooperative Coevolution for Efficient Optimization of Large-Scale Fully-Separable Continuous Functions.\n \n \n \n\n\n \n Bali, K. K.; Chandra, R.; and Omidvar, M. N.\n\n\n \n\n\n\n In ICONIP (3), volume 9491, of Lecture Notes in Computer Science, pages 137–147, 2015. Springer\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/iconip/BaliCO15,\n  author       = {Kavitesh K. Bali and\n                  Rohitash Chandra and\n                  Mohammad Nabi Omidvar},\n  title        = {Competitive Island-Based Cooperative Coevolution for Efficient Optimization\n                  of Large-Scale Fully-Separable Continuous Functions},\n  booktitle    = {{ICONIP} {(3)}},\n  series       = {Lecture Notes in Computer Science},\n  volume       = {9491},\n  pages        = {137--147},\n  publisher    = {Springer},\n  year         = {2015}\n}\n\n
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\n \n\n \n \n \n \n \n Enhancing Competitive Island Cooperative Neuro-Evolution Through Backpropagation for Pattern Classification.\n \n \n \n\n\n \n Wong, G.; and Chandra, R.\n\n\n \n\n\n\n In ICONIP (1), volume 9489, of Lecture Notes in Computer Science, pages 293–301, 2015. Springer\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/iconip/WongC15,\n  author       = {Gary Wong and\n                  Rohitash Chandra},\n  title        = {Enhancing Competitive Island Cooperative Neuro-Evolution Through Backpropagation\n                  for Pattern Classification},\n  booktitle    = {{ICONIP} {(1)}},\n  series       = {Lecture Notes in Computer Science},\n  volume       = {9489},\n  pages        = {293--301},\n  publisher    = {Springer},\n  year         = {2015}\n}\n\n
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\n \n\n \n \n \n \n \n Application of cooperative neuro-evolution of Elman recurrent networks for a two-dimensional cyclone track prediction for the south pacific region.\n \n \n \n\n\n \n Chandra, R.; Dayal, K.; and Rollings, N.\n\n\n \n\n\n\n In IJCNN, pages 1–8, 2015. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/ijcnn/ChandraDR15,\n  author       = {Rohitash Chandra and\n                  Kavina Dayal and\n                  Nicholas Rollings},\n  title        = {Application of cooperative neuro-evolution of Elman recurrent networks\n                  for a two-dimensional cyclone track prediction for the south pacific\n                  region},\n  booktitle    = {{IJCNN}},\n  pages        = {1--8},\n  publisher    = {{IEEE}},\n  year         = {2015}\n}\n\n
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\n \n\n \n \n \n \n \n Competitive two-island cooperative co-evolution for training feedforward neural networks for pattern classification problems.\n \n \n \n\n\n \n Chandra, R.; and Wong, G.\n\n\n \n\n\n\n In IJCNN, pages 1–8, 2015. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/ijcnn/ChandraW15,\n  author       = {Rohitash Chandra and\n                  Gary Wong},\n  title        = {Competitive two-island cooperative co-evolution for training feedforward\n                  neural networks for pattern classification problems},\n  booktitle    = {{IJCNN}},\n  pages        = {1--8},\n  publisher    = {{IEEE}},\n  year         = {2015}\n}\n\n
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\n \n\n \n \n \n \n \n Design of a Mobile Face Recognition System for Visually Impaired Persons.\n \n \n \n\n\n \n Chaudhry, S.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/1502.00756. 2015.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/ChaudhryC15,\n  author       = {Shonal Chaudhry and\n                  Rohitash Chandra},\n  title        = {Design of a Mobile Face Recognition System for Visually Impaired Persons},\n  journal      = {CoRR},\n  volume       = {abs/1502.00756},\n  year         = {2015}\n}\n\n
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\n \n\n \n \n \n \n \n Development of an Android Application for an Electronic Medical Record System in an Outpatient Environment for Healthcare in Fiji.\n \n \n \n\n\n \n Abel, D.; Gavidi, B.; Rollings, N.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/1503.00810. 2015.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/corr/AbelGRC15,\n  author       = {Daryl Abel and\n                  Bulou Gavidi and\n                  Nicholas Rollings and\n                  Rohitash Chandra},\n  title        = {Development of an Android Application for an Electronic Medical Record\n                  System in an Outpatient Environment for Healthcare in Fiji},\n  journal      = {CoRR},\n  volume       = {abs/1503.00810},\n  year         = {2015}\n}\n\n
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\n \n\n \n \n \n \n \n Mobile Application for Dengue Fever Monitoring and Tracking via GPS: Case Study for Fiji.\n \n \n \n\n\n \n Reddy, E.; Kumar, S.; Rollings, N.; and Chandra, R.\n\n\n \n\n\n\n CoRR, abs/1503.00814. 2015.\n \n\n\n\n
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@article{DBLP:journals/corr/ReddyKRC15,\n  author       = {Emmenual Reddy and\n                  Sarnil Kumar and\n                  Nicholas Rollings and\n                  Rohitash Chandra},\n  title        = {Mobile Application for Dengue Fever Monitoring and Tracking via {GPS:}\n                  Case Study for Fiji},\n  journal      = {CoRR},\n  volume       = {abs/1503.00814},\n  year         = {2015}\n}\n\n
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\n \n\n \n \n \n \n \n A Study of the Management of Electronic Medical Records in Fijian Hospitals.\n \n \n \n\n\n \n Ravindra, S. S.; Chandra, R.; and Dhenesh, V. S.\n\n\n \n\n\n\n CoRR, abs/1507.03659. 2015.\n \n\n\n\n
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@article{DBLP:journals/corr/RavindraCD15,\n  author       = {Swaran S. Ravindra and\n                  Rohitash Chandra and\n                  Virallikattur S. Dhenesh},\n  title        = {A Study of the Management of Electronic Medical Records in Fijian\n                  Hospitals},\n  journal      = {CoRR},\n  volume       = {abs/1507.03659},\n  year         = {2015}\n}\n\n
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\n  \n 2014\n \n \n (4)\n \n \n
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\n \n\n \n \n \n \n \n Memetic cooperative coevolution of Elman recurrent neural networks.\n \n \n \n\n\n \n Chandra, R.\n\n\n \n\n\n\n Soft Comput., 18(8): 1549–1559. 2014.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/soco/Chandra14,\n  author       = {Rohitash Chandra},\n  title        = {Memetic cooperative coevolution of Elman recurrent neural networks},\n  journal      = {Soft Comput.},\n  volume       = {18},\n  number       = {8},\n  pages        = {1549--1559},\n  year         = {2014}\n}\n\n
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\n \n\n \n \n \n \n \n Multi-objective cooperative coevolution of neural networks for time series prediction.\n \n \n \n\n\n \n Chand, S.; and Chandra, R.\n\n\n \n\n\n\n In IJCNN, pages 190–197, 2014. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/ijcnn/ChandC14,\n  author       = {Shelvin Chand and\n                  Rohitash Chandra},\n  title        = {Multi-objective cooperative coevolution of neural networks for time\n                  series prediction},\n  booktitle    = {{IJCNN}},\n  pages        = {190--197},\n  publisher    = {{IEEE}},\n  year         = {2014}\n}\n\n
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\n \n\n \n \n \n \n \n Cooperative coevolution of feed forward neural networks for financial time series problem.\n \n \n \n\n\n \n Chand, S.; and Chandra, R.\n\n\n \n\n\n\n In IJCNN, pages 202–209, 2014. IEEE\n \n\n\n\n
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@inproceedings{DBLP:conf/ijcnn/ChandC14a,\n  author       = {Shelvin Chand and\n                  Rohitash Chandra},\n  title        = {Cooperative coevolution of feed forward neural networks for financial\n                  time series problem},\n  booktitle    = {{IJCNN}},\n  pages        = {202--209},\n  publisher    = {{IEEE}},\n  year         = {2014}\n}\n\n
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\n \n\n \n \n \n \n \n Competitive two-island cooperative coevolution for training Elman recurrent networks for time series prediction.\n \n \n \n\n\n \n Chandra, R.\n\n\n \n\n\n\n In IJCNN, pages 565–572, 2014. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/ijcnn/Chandra14,\n  author       = {Rohitash Chandra},\n  title        = {Competitive two-island cooperative coevolution for training Elman\n                  recurrent networks for time series prediction},\n  booktitle    = {{IJCNN}},\n  pages        = {565--572},\n  publisher    = {{IEEE}},\n  year         = {2014}\n}\n\n
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\n  \n 2013\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n Adaptive problem decomposition in cooperative coevolution of recurrent networks for time series prediction.\n \n \n \n\n\n \n Chandra, R.\n\n\n \n\n\n\n In IJCNN, pages 1–8, 2013. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/ijcnn/Chandra13,\n  author       = {Rohitash Chandra},\n  title        = {Adaptive problem decomposition in cooperative coevolution of recurrent\n                  networks for time series prediction},\n  booktitle    = {{IJCNN}},\n  pages        = {1--8},\n  publisher    = {{IEEE}},\n  year         = {2013}\n}\n\n
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\n  \n 2012\n \n \n (6)\n \n \n
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\n \n\n \n \n \n \n \n Problem Decomposition and Adaptation in Cooperative Neuro-Evolution.\n \n \n \n\n\n \n Chandra, R.\n\n\n \n\n\n\n Ph.D. Thesis, Victoria University of Wellington, New Zealand, 2012.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@phdthesis{DBLP:phd/basesearch/Chandra12,\n  author       = {Rohitash Chandra},\n  title        = {Problem Decomposition and Adaptation in Cooperative Neuro-Evolution},\n  school       = {Victoria University of Wellington, New Zealand},\n  year         = {2012}\n}\n\n
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\n \n\n \n \n \n \n \n Crossover-based local search in cooperative co-evolutionary feedforward neural networks.\n \n \n \n\n\n \n Chandra, R.; Frean, M. R.; and Zhang, M.\n\n\n \n\n\n\n Appl. Soft Comput., 12(9): 2924–2932. 2012.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/asc/ChandraFZ12,\n  author       = {Rohitash Chandra and\n                  Marcus R. Frean and\n                  Mengjie Zhang},\n  title        = {Crossover-based local search in cooperative co-evolutionary feedforward\n                  neural networks},\n  journal      = {Appl. Soft Comput.},\n  volume       = {12},\n  number       = {9},\n  pages        = {2924--2932},\n  year         = {2012}\n}\n\n
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\n \n\n \n \n \n \n \n Cooperative coevolution of Elman recurrent neural networks for chaotic time series prediction.\n \n \n \n\n\n \n Chandra, R.; and Zhang, M.\n\n\n \n\n\n\n Neurocomputing, 86: 116–123. 2012.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/ijon/ChandraZ12,\n  author       = {Rohitash Chandra and\n                  Mengjie Zhang},\n  title        = {Cooperative coevolution of Elman recurrent neural networks for chaotic\n                  time series prediction},\n  journal      = {Neurocomputing},\n  volume       = {86},\n  pages        = {116--123},\n  year         = {2012}\n}\n\n
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\n \n\n \n \n \n \n \n On the issue of separability for problem decomposition in cooperative neuro-evolution.\n \n \n \n\n\n \n Chandra, R.; Frean, M. R.; and Zhang, M.\n\n\n \n\n\n\n Neurocomputing, 87: 33–40. 2012.\n \n\n\n\n
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@article{DBLP:journals/ijon/ChandraFZ12,\n  author       = {Rohitash Chandra and\n                  Marcus R. Frean and\n                  Mengjie Zhang},\n  title        = {On the issue of separability for problem decomposition in cooperative\n                  neuro-evolution},\n  journal      = {Neurocomputing},\n  volume       = {87},\n  pages        = {33--40},\n  year         = {2012}\n}\n\n
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\n \n\n \n \n \n \n \n Adapting modularity during learning in cooperative co-evolutionary recurrent neural networks.\n \n \n \n\n\n \n Chandra, R.; Frean, M. R.; and Zhang, M.\n\n\n \n\n\n\n Soft Comput., 16(6): 1009–1020. 2012.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{DBLP:journals/soco/ChandraFZ12,\n  author       = {Rohitash Chandra and\n                  Marcus R. Frean and\n                  Mengjie Zhang},\n  title        = {Adapting modularity during learning in cooperative co-evolutionary\n                  recurrent neural networks},\n  journal      = {Soft Comput.},\n  volume       = {16},\n  number       = {6},\n  pages        = {1009--1020},\n  year         = {2012}\n}\n\n
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\n \n\n \n \n \n \n \n Application of Cooperative Convolution Optimization for 13C Metabolic Flux Analysis: Simulation of Isotopic Labeling Patterns Based on Tandem Mass Spectrometry Measurements.\n \n \n \n\n\n \n Chandra, R.; Zhang, M.; and Peng, L.\n\n\n \n\n\n\n In SEAL, volume 7673, of Lecture Notes in Computer Science, pages 178–187, 2012. Springer\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/seal/ChandraZP12,\n  author       = {Rohitash Chandra and\n                  Mengjie Zhang and\n                  Lifeng Peng},\n  title        = {Application of Cooperative Convolution Optimization for 13C Metabolic\n                  Flux Analysis: Simulation of Isotopic Labeling Patterns Based on Tandem\n                  Mass Spectrometry Measurements},\n  booktitle    = {{SEAL}},\n  series       = {Lecture Notes in Computer Science},\n  volume       = {7673},\n  pages        = {178--187},\n  publisher    = {Springer},\n  year         = {2012}\n}\n\n
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\n  \n 2011\n \n \n (4)\n \n \n
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\n \n\n \n \n \n \n \n On solving the forward kinematics of 3RPR planar parallel manipulator using hybrid metaheuristics.\n \n \n \n\n\n \n Chandra, R.; and Rolland, L.\n\n\n \n\n\n\n Appl. Math. Comput., 217(22): 8997–9008. 2011.\n \n\n\n\n
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@article{DBLP:journals/amc/ChandraR11,\n  author       = {Rohitash Chandra and\n                  Luc Rolland},\n  title        = {On solving the forward kinematics of 3RPR planar parallel manipulator\n                  using hybrid metaheuristics},\n  journal      = {Appl. Math. Comput.},\n  volume       = {217},\n  number       = {22},\n  pages        = {8997--9008},\n  year         = {2011}\n}\n\n
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\n \n\n \n \n \n \n \n Encoding subcomponents in cooperative co-evolutionary recurrent neural networks.\n \n \n \n\n\n \n Chandra, R.; Frean, M. R.; Zhang, M.; and Omlin, C. W.\n\n\n \n\n\n\n Neurocomputing, 74(17): 3223–3234. 2011.\n \n\n\n\n
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@article{DBLP:journals/ijon/ChandraFZO11,\n  author       = {Rohitash Chandra and\n                  Marcus R. Frean and\n                  Mengjie Zhang and\n                  Christian W. Omlin},\n  title        = {Encoding subcomponents in cooperative co-evolutionary recurrent neural\n                  networks},\n  journal      = {Neurocomputing},\n  volume       = {74},\n  number       = {17},\n  pages        = {3223--3234},\n  year         = {2011}\n}\n\n
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\n \n\n \n \n \n \n \n A memetic framework for cooperative coevolution of recurrent neural networks.\n \n \n \n\n\n \n Chandra, R.; Frean, M. R.; and Zhang, M.\n\n\n \n\n\n\n In IJCNN, pages 673–680, 2011. IEEE\n \n\n\n\n
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@inproceedings{DBLP:conf/ijcnn/ChandraFZ11,\n  author       = {Rohitash Chandra and\n                  Marcus R. Frean and\n                  Mengjie Zhang},\n  title        = {A memetic framework for cooperative coevolution of recurrent neural\n                  networks},\n  booktitle    = {{IJCNN}},\n  pages        = {673--680},\n  publisher    = {{IEEE}},\n  year         = {2011}\n}\n\n
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\n \n\n \n \n \n \n \n Modularity adaptation in cooperative coevolution of feedforward neural networks.\n \n \n \n\n\n \n Chandra, R.; Frean, M. R.; and Zhang, M.\n\n\n \n\n\n\n In IJCNN, pages 681–688, 2011. IEEE\n \n\n\n\n
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@inproceedings{DBLP:conf/ijcnn/ChandraFZ11a,\n  author       = {Rohitash Chandra and\n                  Marcus R. Frean and\n                  Mengjie Zhang},\n  title        = {Modularity adaptation in cooperative coevolution of feedforward neural\n                  networks},\n  booktitle    = {{IJCNN}},\n  pages        = {681--688},\n  publisher    = {{IEEE}},\n  year         = {2011}\n}\n\n
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\n  \n 2010\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n An Encoding Scheme for Cooperative Coevolutionary Feedforward Neural Networks.\n \n \n \n\n\n \n Chandra, R.; Frean, M. R.; and Zhang, M.\n\n\n \n\n\n\n In Australasian Conference on Artificial Intelligence, volume 6464, of Lecture Notes in Computer Science, pages 253–262, 2010. Springer\n \n\n\n\n
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@inproceedings{DBLP:conf/ausai/ChandraFZ10,\n  author       = {Rohitash Chandra and\n                  Marcus R. Frean and\n                  Mengjie Zhang},\n  title        = {An Encoding Scheme for Cooperative Coevolutionary Feedforward Neural\n                  Networks},\n  booktitle    = {Australasian Conference on Artificial Intelligence},\n  series       = {Lecture Notes in Computer Science},\n  volume       = {6464},\n  pages        = {253--262},\n  publisher    = {Springer},\n  year         = {2010}\n}\n\n
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\n  \n 2009\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n A meta-heuristic paradigm for solving the forward kinematics of 6-6 general parallel manipulator.\n \n \n \n\n\n \n Chandra, R.; Frean, M. R.; and Rolland, L.\n\n\n \n\n\n\n In CIRA, pages 171–176, 2009. IEEE\n \n\n\n\n
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@inproceedings{DBLP:conf/cira/ChandraFR09,\n  author       = {Rohitash Chandra and\n                  Marcus R. Frean and\n                  Luc Rolland},\n  title        = {A meta-heuristic paradigm for solving the forward kinematics of 6-6\n                  general parallel manipulator},\n  booktitle    = {{CIRA}},\n  pages        = {171--176},\n  publisher    = {{IEEE}},\n  year         = {2009}\n}\n\n
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\n \n\n \n \n \n \n \n Solving the forward kinematics of the 3RPR planar parallel manipulator using a hybrid meta-heuristic paradigm.\n \n \n \n\n\n \n Chandra, R.; Zhang, M.; and Rolland, L.\n\n\n \n\n\n\n In CIRA, pages 177–182, 2009. IEEE\n \n\n\n\n
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@inproceedings{DBLP:conf/cira/ChandraZR09,\n  author       = {Rohitash Chandra and\n                  Mengjie Zhang and\n                  Luc Rolland},\n  title        = {Solving the forward kinematics of the 3RPR planar parallel manipulator\n                  using a hybrid meta-heuristic paradigm},\n  booktitle    = {{CIRA}},\n  pages        = {177--182},\n  publisher    = {{IEEE}},\n  year         = {2009}\n}\n\n
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\n \n\n \n \n \n \n \n Forward kinematics of the 3RPR planar parallel manipulators using real coded genetic algorithms.\n \n \n \n\n\n \n Rolland, L.; and Chandra, R.\n\n\n \n\n\n\n In ISCIS, pages 381–386, 2009. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/iscis/RollandC09,\n  author       = {Luc Rolland and\n                  Rohitash Chandra},\n  title        = {Forward kinematics of the 3RPR planar parallel manipulators using\n                  real coded genetic algorithms},\n  booktitle    = {{ISCIS}},\n  pages        = {381--386},\n  publisher    = {{IEEE}},\n  year         = {2009}\n}\n\n
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\n  \n 2008\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n Hybrid Evolutionary One-Step Gradient Descent for Training Recurrent Neural Networks.\n \n \n \n\n\n \n Chandra, R.; and Omlin, C. W.\n\n\n \n\n\n\n In GEM, pages 305–311, 2008. CSREA Press\n \n\n\n\n
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@inproceedings{DBLP:conf/gem/ChandraO08,\n  author       = {Rohitash Chandra and\n                  Christian W. Omlin},\n  title        = {Hybrid Evolutionary One-Step Gradient Descent for Training Recurrent\n                  Neural Networks},\n  booktitle    = {{GEM}},\n  pages        = {305--311},\n  publisher    = {{CSREA} Press},\n  year         = {2008}\n}\n\n
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\n  \n 2007\n \n \n (4)\n \n \n
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\n \n\n \n \n \n \n \n A Hybrid Recurrent Neural Networks Architecture Inspired by Hidden Markov Models: Training and Extraction of Deterministic Finite Automaton.\n \n \n \n\n\n \n Chandra, R.; and Omlin, C. W.\n\n\n \n\n\n\n In Artificial Intelligence and Pattern Recognition, pages 278–285, 2007. ISRST\n \n\n\n\n
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@inproceedings{DBLP:conf/aiprf/ChandraO07,\n  author       = {Rohitash Chandra and\n                  Christian W. Omlin},\n  title        = {A Hybrid Recurrent Neural Networks Architecture Inspired by Hidden\n                  Markov Models: Training and Extraction of Deterministic Finite Automaton},\n  booktitle    = {Artificial Intelligence and Pattern Recognition},\n  pages        = {278--285},\n  publisher    = {{ISRST}},\n  year         = {2007}\n}\n\n
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\n \n\n \n \n \n \n \n The Comparison and Combination of Genetic and Gradient Descent Learning in Recurrent Neural Networks: An Application to Speech Phoneme Classification.\n \n \n \n\n\n \n Chandra, R.; and Omlin, C. W.\n\n\n \n\n\n\n In Artificial Intelligence and Pattern Recognition, pages 286–293, 2007. ISRST\n \n\n\n\n
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@inproceedings{DBLP:conf/aiprf/ChandraO07a,\n  author       = {Rohitash Chandra and\n                  Christian W. Omlin},\n  title        = {The Comparison and Combination of Genetic and Gradient Descent Learning\n                  in Recurrent Neural Networks: An Application to Speech Phoneme Classification},\n  booktitle    = {Artificial Intelligence and Pattern Recognition},\n  pages        = {286--293},\n  publisher    = {{ISRST}},\n  year         = {2007}\n}\n\n
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\n \n\n \n \n \n \n \n Knowledge Discovery using Artificial Neural Networks for a Conservation Biology Domain.\n \n \n \n\n\n \n Chandra, R.; and Omlin, C. W.\n\n\n \n\n\n\n In DMIN, pages 221–227, 2007. CSREA Press\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{DBLP:conf/dmin/ChandraO07,\n  author       = {Rohitash Chandra and\n                  Christian W. Omlin},\n  title        = {Knowledge Discovery using Artificial Neural Networks for a Conservation\n                  Biology Domain},\n  booktitle    = {{DMIN}},\n  pages        = {221--227},\n  publisher    = {{CSREA} Press},\n  year         = {2007}\n}\n\n
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\n \n\n \n \n \n \n \n Hybrid Recurrent Neural Networks: An Application to Phoneme Classification.\n \n \n \n\n\n \n Chandra, R.; and Omlin, C. W.\n\n\n \n\n\n\n In GEM, pages 57–62, 2007. CSREA Press\n \n\n\n\n
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@inproceedings{DBLP:conf/gem/ChandraO07,\n  author       = {Rohitash Chandra and\n                  Christian W. Omlin},\n  title        = {Hybrid Recurrent Neural Networks: An Application to Phoneme Classification},\n  booktitle    = {{GEM}},\n  pages        = {57--62},\n  publisher    = {{CSREA} Press},\n  year         = {2007}\n}\n\n
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\n  \n 2006\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n Training and extraction of fuzzy finite state automata in recurrent neural networks.\n \n \n \n\n\n \n Chandra, R.; and Omlin, C. W.\n\n\n \n\n\n\n In Computational Intelligence, pages 274–279, 2006. IASTED/ACTA Press\n \n\n\n\n
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@inproceedings{DBLP:conf/iastedCI/ChandraO06,\n  author       = {Rohitash Chandra and\n                  Christian W. Omlin},\n  title        = {Training and extraction of fuzzy finite state automata in recurrent\n                  neural networks},\n  booktitle    = {Computational Intelligence},\n  pages        = {274--279},\n  publisher    = {{IASTED/ACTA} Press},\n  year         = {2006}\n}\n\n
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