A closer look at memorization in deep networks D Arpit, S Jastrzębski, N Ballas, D Krueger, E Bengio, MS Kanwal, ... International conference on machine learning, 233-242, 2017 | 2110 | 2017 |
Combining modality specific deep neural networks for emotion recognition in video SE Kahou, C Pal, X Bouthillier, P Froumenty, Ç Gülçehre, R Memisevic, ... Proceedings of the 15th ACM on International conference on multimodal …, 2013 | 444 | 2013 |
Conditional computation in neural networks for faster models E Bengio, PL Bacon, J Pineau, D Precup arXiv preprint arXiv:1511.06297, 2015 | 360 | 2015 |
Flow network based generative models for non-iterative diverse candidate generation E Bengio, M Jain, M Korablyov, D Precup, Y Bengio Advances in Neural Information Processing Systems 34, 27381-27394, 2021 | 287 | 2021 |
Gflownet foundations Y Bengio, S Lahlou, T Deleu, EJ Hu, M Tiwari, E Bengio The Journal of Machine Learning Research 24 (1), 10006-10060, 2023 | 197 | 2023 |
Biological sequence design with gflownets M Jain, E Bengio, A Hernandez-Garcia, J Rector-Brooks, BFP Dossou, ... International Conference on Machine Learning, 9786-9801, 2022 | 158 | 2022 |
Trajectory balance: Improved credit assignment in gflownets N Malkin, M Jain, E Bengio, C Sun, Y Bengio Advances in Neural Information Processing Systems 35, 5955-5967, 2022 | 135 | 2022 |
Independently controllable factors V Thomas, J Pondard, E Bengio, M Sarfati, P Beaudoin, MJ Meurs, ... arXiv preprint arXiv:1708.01289, 2017 | 98 | 2017 |
Deep nets don't learn via memorization D Krueger, N Ballas, S Jastrzebski, D Arpit, MS Kanwal, T Maharaj, ... | 75 | 2017 |
Interference and generalization in temporal difference learning E Bengio, J Pineau, D Precup International Conference on Machine Learning, 767-777, 2020 | 71 | 2020 |
Disentangling the independently controllable factors of variation by interacting with the world V Thomas, E Bengio, W Fedus, J Pondard, P Beaudoin, H Larochelle, ... arXiv preprint arXiv:1802.09484, 2018 | 69 | 2018 |
Multi-objective gflownets M Jain, SC Raparthy, A Hernández-Garcıa, J Rector-Brooks, Y Bengio, ... International conference on machine learning, 14631-14653, 2023 | 65 | 2023 |
Learning gflownets from partial episodes for improved convergence and stability K Madan, J Rector-Brooks, M Korablyov, E Bengio, M Jain, AC Nica, ... International Conference on Machine Learning, 23467-23483, 2023 | 64 | 2023 |
Independently controllable features E Bengio, V Thomas, J Pineau, D Precup, Y Bengio arXiv preprint arXiv:1703.07718, 2017 | 46 | 2017 |
Towards understanding and improving gflownet training MW Shen, E Bengio, E Hajiramezanali, A Loukas, K Cho, T Biancalani International Conference on Machine Learning, 30956-30975, 2023 | 39 | 2023 |
World knowledge for reading comprehension: Rare entity prediction with hierarchical lstms using external descriptions T Long, E Bengio, R Lowe, JCK Cheung, D Precup Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017 | 37 | 2017 |
Evaluating generalization in gflownets for molecule design AC Nica, M Jain, E Bengio, CH Liu, M Korablyov, MM Bronstein, Y Bengio ICLR2022 Machine Learning for Drug Discovery, 2022 | 22 | 2022 |
Local search gflownets M Kim, T Yun, E Bengio, D Zhang, Y Bengio, S Ahn, J Park arXiv preprint arXiv:2310.02710, 2023 | 20 | 2023 |
Learning to scale logits for temperature-conditional gflownets M Kim, J Ko, T Yun, D Zhang, L Pan, W Kim, J Park, E Bengio, Y Bengio arXiv preprint arXiv:2310.02823, 2023 | 13 | 2023 |
Correcting momentum in temporal difference learning E Bengio, J Pineau, D Precup arXiv preprint arXiv:2106.03955, 2021 | 13 | 2021 |