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\n  \n 2020\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n Temporal Attribute Prediction via Joint Modeling of Multi-Relational Structure Evolution.\n \n \n \n\n\n \n Garg, S.; Sharma, N.; Jin, W.; and Ren, X.\n\n\n \n\n\n\n In 2020. \n \n\n\n\n
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@inproceedings{garg2020temporal,\n    author = {Sankalp Garg and Navodita Sharma and Woojeong Jin and Xiang Ren},\n    title = {Temporal Attribute Prediction via Joint Modeling of Multi-Relational Structure Evolution},\n    year = {2020},\n\teprint={2003.03919},\n\tarchivePrefix={arXiv},\n\tprimaryClass={cs.LG}\n}\n\n
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\n \n\n \n \n \n \n \n Query2box: Reasoning over Knowledge Graphs in Vector Space using Box Embeddings.\n \n \n \n\n\n \n Ren, H.; Hu, W.; and Leskovec, J.\n\n\n \n\n\n\n In 2020. \n \n\n\n\n
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@inproceedings{ren2020query2box,\ntitle={Query2box: Reasoning over Knowledge Graphs in Vector Space using Box Embeddings},\nauthor={Hongyu Ren and Weihua Hu and Jure Leskovec},\nyear={2020},\neprint={2002.05969},\narchivePrefix={arXiv},\nprimaryClass={cs.LG}\n}\n\n
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\n  \n 2019\n \n \n (11)\n \n \n
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\n \n\n \n \n \n \n \n CommonGen: A Constrained Text Generation Dataset Towards Generative Commonsense Reasoning.\n \n \n \n\n\n \n Lin, B. Y.; Shen, M.; Xing, Y.; Zhou, P.; and Ren, X.\n\n\n \n\n\n\n In 2019. \n \n\n\n\n
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@inproceedings{lin2019commongen,\n\ttitle={CommonGen: A Constrained Text Generation Dataset Towards Generative Commonsense Reasoning},\n\tauthor={Bill Yuchen Lin and Ming Shen and Yu Xing and Pei Zhou and Xiang Ren},\n\tyear={2019},\n\teprint={1911.03705},\n\tarchivePrefix={arXiv},\n\tprimaryClass={cs.CL}\n}\n\n
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\n \n\n \n \n \n \n \n Learning from Explanations with Neural Execution Tree.\n \n \n \n\n\n \n Wang, Z.; Qin, Y.; Zhou, W.; Yan, J.; Ye, Q.; Neves, L.; Liu, Z.; and Ren, X.\n\n\n \n\n\n\n arXiv e-prints,arXiv:1911.01352. November 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 \n\n\n\n
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@ARTICLE{2019arXiv191101352W,\n\tauthor = {{Wang}, Ziqi and {Qin}, Yujia and {Zhou}, Wenxuan and {Yan}, Jun and\n         {Ye}, Qinyuan and {Neves}, Leonardo and {Liu}, Zhiyuan and {Ren}, Xiang},\n\ttitle = "{Learning from Explanations with Neural Execution Tree}",\n\tjournal = {arXiv e-prints},\n\tkeywords = {Computer Science - Computation and Language, I.2.7},\n\tyear = 2019,\n\tmonth = nov,\n\teid = {arXiv:1911.01352},\n\tpages = {arXiv:1911.01352},\n\tarchivePrefix = {arXiv},\n\teprint = {1911.01352},\n\tprimaryClass = {cs.CL},\n\tadsurl = {https://ui.adsabs.harvard.edu/abs/2019arXiv191101352W},\n\tadsnote = {Provided by the SAO/NASA Astrophysics Data System}\n}\n\n
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\n \n\n \n \n \n \n \n NERO: A Neural Rule Grounding Framework for Label-Efficient Relation Extraction.\n \n \n \n\n\n \n Zhou, W.; Lin, H.; Lin, B. Y.; Wang, Z.; Du, J.; Neves, L.; and Ren, X.\n\n\n \n\n\n\n In 2019. \n \n\n\n\n
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@inproceedings{zhou2019nero,\ntitle={NERO: A Neural Rule Grounding Framework for Label-Efficient Relation Extraction},\nauthor={Wenxuan Zhou and Hongtao Lin and Bill Yuchen Lin and Ziqi Wang and Junyi Du and Leonardo Neves and Xiang Ren},\nyear={2019},\neprint={1909.02177},\narchivePrefix={arXiv},\nprimaryClass={cs.CL}\n}\n\n
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\n \n\n \n \n \n \n \n KagNet: Knowledge-Aware Graph Networks for Commonsense Reasoning.\n \n \n \n\n\n \n Lin, B. Y.; Chen, X.; Chen, J.; and Ren, X.\n\n\n \n\n\n\n In 2019. \n \n\n\n\n
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@inproceedings{lin2019kagnet,\ntitle={KagNet: Knowledge-Aware Graph Networks for Commonsense Reasoning},\nauthor={Bill Yuchen Lin and Xinyue Chen and Jamin Chen and Xiang Ren},\nyear={2019},\neprint={1909.02151},\narchivePrefix={arXiv},\nprimaryClass={cs.CL}\n}\n\n
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\n \n\n \n \n \n \n \n Collaborative Policy Learning for Open Knowledge Graph Reasoning.\n \n \n \n\n\n \n Fu, C.; Chen, T.; Qu, M.; Jin, W.; and Ren, X.\n\n\n \n\n\n\n In 2019. \n \n\n\n\n
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@inproceedings{fu2019collaborative,\ntitle={Collaborative Policy Learning for Open Knowledge Graph Reasoning},\nauthor={Cong Fu and Tong Chen and Meng Qu and Woojeong Jin and Xiang Ren},\nyear={2019},\neprint={1909.00230},\narchivePrefix={arXiv},\nprimaryClass={cs.AI}\n}\n\n
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\n \n\n \n \n \n \n \n Selection via Proxy: Efficient Data Selection for Deep Learning.\n \n \n \n\n\n \n Coleman, C.; Yeh, C.; Mussmann, S.; Mirzasoleiman, B.; Bailis, P.; Liang, P.; Leskovec, J.; and Zaharia, M.\n\n\n \n\n\n\n In 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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@inproceedings{coleman2019selection,\ntitle={Selection via Proxy: Efficient Data Selection for Deep Learning},\nauthor={Cody Coleman and Christopher Yeh and Stephen Mussmann and Baharan Mirzasoleiman and Peter Bailis and Percy Liang and Jure Leskovec and Matei Zaharia},\nyear={2019},\neprint={1906.11829},\narchivePrefix={arXiv},\nprimaryClass={cs.LG}\n}\n\n
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\n \n\n \n \n \n \n \n \n GNNExplainer: Generating Explanations for Graph Neural Networks.\n \n \n \n \n\n\n \n Ying, Z.; Bourgeois, D.; You, J.; Zitnik, M.; and Leskovec, J.\n\n\n \n\n\n\n In Wallach, H.; Larochelle, H.; Beygelzimer, A.; d' Alché-Buc, F.; Fox, E.; and Garnett, R., editor(s), Advances in Neural Information Processing Systems 32, pages 9244–9255. Curran Associates, Inc., 2019.\n \n\n\n\n
\n\n\n\n \n \n \"GNNExplainer:Paper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 4 downloads\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@incollection{NIPS2019_9123,\ntitle = {GNNExplainer: Generating Explanations for Graph Neural Networks},\nauthor = {Ying, Zhitao and Bourgeois, Dylan and You, Jiaxuan and Zitnik, Marinka and Leskovec, Jure},\nbooktitle = {Advances in Neural Information Processing Systems 32},\neditor = {H. Wallach and H. Larochelle and A. Beygelzimer and F. d\\textquotesingle Alch\\'{e}-Buc and E. Fox and R. Garnett},\npages = {9244--9255},\nyear = {2019},\npublisher = {Curran Associates, Inc.},\nurl = {http://papers.nips.cc/paper/9123-gnnexplainer-generating-explanations-for-graph-neural-networks.pdf}\n}\n\n
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\n \n\n \n \n \n \n \n Hyperbolic Graph Convolutional Neural Networks.\n \n \n \n\n\n \n Chami, I.; Ying, R.; Ré, C.; and Leskovec, J.\n\n\n \n\n\n\n In 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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@inproceedings{chami2019hyperbolic,\ntitle={Hyperbolic Graph Convolutional Neural Networks},\nauthor={Ines Chami and Rex Ying and Christopher Ré and Jure Leskovec},\nyear={2019},\neprint={1910.12933},\narchivePrefix={arXiv},\nprimaryClass={cs.LG}\n}\n\n
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\n \n\n \n \n \n \n \n \n Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks.\n \n \n \n \n\n\n \n Kumar, S.; Zhang, X.; and Leskovec, J.\n\n\n \n\n\n\n In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, of KDD ’19, pages 1269–1278, New York, NY, USA, 2019. Association for Computing Machinery\n \n\n\n\n
\n\n\n\n \n \n \"PredictingPaper\n  \n \n\n \n \n doi\n  \n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 4 downloads\n \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{10.1145/3292500.3330895,\nauthor = {Kumar, Srijan and Zhang, Xikun and Leskovec, Jure},\ntitle = {Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks},\nyear = {2019},\nisbn = {9781450362016},\npublisher = {Association for Computing Machinery},\naddress = {New York, NY, USA},\nurl = {https://doi.org/10.1145/3292500.3330895},\ndoi = {10.1145/3292500.3330895},\nbooktitle = {Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining},\npages = {1269–1278},\nnumpages = {10},\nkeywords = {deep learning, embeddings},\nlocation = {Anchorage, AK, USA},\nseries = {KDD ’19}\n}\n\n
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\n \n\n \n \n \n \n \n Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems.\n \n \n \n\n\n \n Wang, H.; Zhang, F.; Zhang, M.; Leskovec, J.; Zhao, M.; Li, W.; and Wang, Z.\n\n\n \n\n\n\n In 2019. \n \n\n\n\n
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@inproceedings{wang2019knowledgeaware,\ntitle={Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems},\nauthor={Hongwei Wang and Fuzheng Zhang and Mengdi Zhang and Jure Leskovec and Miao Zhao and Wenjie Li and Zhongyuan Wang},\nyear={2019},\neprint={1905.04413},\narchivePrefix={arXiv},\nprimaryClass={cs.LG}\n}\n\n
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\n \n\n \n \n \n \n \n Position-aware Graph Neural Networks.\n \n \n \n\n\n \n You, J.; Ying, R.; and Leskovec, J.\n\n\n \n\n\n\n In 2019. \n \n\n\n\n
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@inproceedings{you2019positionaware,\ntitle={Position-aware Graph Neural Networks},\nauthor={Jiaxuan You and Rex Ying and Jure Leskovec},\nyear={2019},\neprint={1906.04817},\narchivePrefix={arXiv},\nprimaryClass={cs.LG}\n}
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