var bibbase_data = {"data":"\"Loading..\"\n\n
\n\n \n\n \n\n \n \n\n \n\n \n \n\n \n\n \n
\n generated by\n \n \"bibbase.org\"\n\n \n
\n \n\n
\n\n \n\n\n
\n\n Excellent! Next you can\n create a new website with this list, or\n embed it in an existing web page by copying & pasting\n any of the following snippets.\n\n
\n JavaScript\n (easiest)\n
\n \n <script src=\"https://bibbase.org/show?bib=https://bibbase.org/f/eigNBhSMoESt5Ygkm/preprints.bib&jsonp=1&jsonp=1\"></script>\n \n
\n\n PHP\n
\n \n <?php\n $contents = file_get_contents(\"https://bibbase.org/show?bib=https://bibbase.org/f/eigNBhSMoESt5Ygkm/preprints.bib&jsonp=1\");\n print_r($contents);\n ?>\n \n
\n\n iFrame\n (not recommended)\n
\n \n <iframe src=\"https://bibbase.org/show?bib=https://bibbase.org/f/eigNBhSMoESt5Ygkm/preprints.bib&jsonp=1\"></iframe>\n \n
\n\n

\n For more details see the documention.\n

\n
\n
\n\n
\n\n This is a preview! To use this list on your own web site\n or create a new web site from it,\n create a free account. The file will be added\n and you will be able to edit it in the File Manager.\n We will show you instructions once you've created your account.\n
\n\n
\n\n

To the site owner:

\n\n

Action required! Mendeley is changing its\n API. In order to keep using Mendeley with BibBase past April\n 14th, you need to:\n

    \n
  1. renew the authorization for BibBase on Mendeley, and
    2. \n
  2. update the BibBase URL\n in your page the same way you did when you initially set up\n this page.\n
    3. \n
\n

\n\n

\n \n \n Fix it now\n

\n
\n\n
\n\n\n
\n \n \n
\n
\n  \n 2023\n \n \n (3)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Weighted Ensemble Models Are Strong Continual Learners.\n \n \n \n \n\n\n \n Marouf, I. E.; Roy, S.; Tartaglione, E.; and Lathuilière, S.\n\n\n \n\n\n\n arXiv preprint arXiv:2312.08977. 2023.\n \n\n\n\n
\n\n\n\n \n \n \"WeightedPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{marouf2023weighted,\n  title={Weighted Ensemble Models Are Strong Continual Learners},\n  author={Marouf, Imad Eddine and Roy, Subhankar and Tartaglione, Enzo and Lathuili{\\`e}re, St{\\'e}phane},\n  journal={arXiv preprint arXiv:2312.08977},\n  year={2023},\n  url={https://arxiv.org/pdf/2312.08977.pdf}\n}\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Enhanced EEG-Based Mental State Classification: A novel approach to eliminate data leakage and improve training optimization for Machine Learning.\n \n \n \n \n\n\n \n Girard, M.; Nahon, R.; Tartaglione, E.; and Nguyen, V.\n\n\n \n\n\n\n arXiv preprint arXiv:2312.09379. 2023.\n \n\n\n\n
\n\n\n\n \n \n \"EnhancedPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{girard2023enhanced,\n  title={Enhanced EEG-Based Mental State Classification: A novel approach to eliminate data leakage and improve training optimization for Machine Learning},\n  author={Girard, Maxime and Nahon, R{\\'e}mi and Tartaglione, Enzo and Nguyen, Van-Tam},\n  journal={arXiv preprint arXiv:2312.09379},\n  year={2023},\n  url={https://arxiv.org/pdf/2312.09379.pdf}\n}\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n Rethinking Class-incremental Learning in the Era of Large Pre-trained Models via Test-Time Adaptation.\n \n \n \n \n\n\n \n Marouf, I. E.; Roy, S.; Tartaglione, E.; and Lathuilière, S.\n\n\n \n\n\n\n arXiv preprint arXiv:2310.11482. 2023.\n \n\n\n\n
\n\n\n\n \n \n \"RethinkingPaper\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 
@article{marouf2023rethinking,\n  title={Rethinking Class-incremental Learning in the Era of Large Pre-trained Models via Test-Time Adaptation},\n  author={Marouf, Imad Eddine and Roy, Subhankar and Tartaglione, Enzo and Lathuili{\\`e}re, St{\\'e}phane},\n  journal={arXiv preprint arXiv:2310.11482},\n  year={2023},\n  url={https://arxiv.org/pdf/2310.11482.pdf}\n}\n
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n
\n
\n  \n 2022\n \n \n (2)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n \n Unsupervised Learning of Unbiased Visual Representations.\n \n \n \n \n\n\n \n Barbano, C. A.; Tartaglione, E.; and Grangetto, M.\n\n\n \n\n\n\n arXiv preprint arXiv:2204.12941. 2022.\n \n\n\n\n
\n\n\n\n \n \n \"UnsupervisedPaper\n  \n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n  \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@article{barbano2022unsupervised,\n  title={Unsupervised Learning of Unbiased Visual Representations},\n  author={Barbano, Carlo Alberto and Tartaglione, Enzo and Grangetto, Marco},\n  journal={arXiv preprint arXiv:2204.12941},\n  year={2022},\n  url={https://arxiv.org/pdf/2204.12941.pdf}\n}\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n \n REM: Routing Entropy Minimization for Capsule Networks.\n \n \n \n \n\n\n \n Renzulli, R.; Tartaglione, E.; and Grangetto, M.\n\n\n \n\n\n\n arXiv preprint arXiv:2204.01298. 2022.\n \n\n\n\n
\n\n\n\n \n \n \"REM:Paper\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 
@article{renzulli2022rem,\n  title={REM: Routing Entropy Minimization for Capsule Networks},\n  author={Renzulli, Riccardo and Tartaglione, Enzo and Grangetto, Marco},\n  journal={arXiv preprint arXiv:2204.01298},\n  year={2022},\n  url={https://arxiv.org/pdf/2204.01298.pdf}\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 \n \n\n
\n"}; document.write(bibbase_data.data);