| Deep Graph Infomax. P Velickovic, W Fedus, WL Hamilton, P Liņ, Y Bengio, RD Hjelm ICLR (Poster) 2 (3), 4, 2019 | 806 | 2019 |
| MaskGAN: Better Text Generation via Filling in the ______ W Fedus, I Goodfellow, AM Dai International Conference on Learning Representations (ICLR 2018), 2018 | 450 | 2018 |
| In silico labeling: Predicting fluorescent labels in unlabeled images SF Eric Christiansen, Samuel J. Yang, D. Michael Ando, Ashkan Javaherian ... Cell, 2018 | 412 | 2018 |
| Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity W Fedus, B Zoph, N Shazeer | 396 | 2021 |
| Deep graph infomax P Veličković, W Fedus, WL Hamilton, P Liņ, Y Bengio, RD Hjelm arXiv preprint arXiv:1809.10341, 2018 | 263 | 2018 |
| The case for a directional dark matter detector and the status of current experimental efforts S Ahlen, N Afshordi, JBR Battat, J Billard, N Bozorgnia, S Burgos, ... International Journal of Modern Physics A 25 (01), 1-51, 2010 | 235 | 2010 |
| Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step W Fedus, M Rosca, B Lakshminarayanan, AM Dai, S Mohamed, ... International Conference on Learning Representations (ICLR 2018), 2017 | 188 | 2017 |
| Language GANs Falling Short M Caccia, L Caccia, W Fedus, H Larochelle, J Pineau, L Charlin International Conference on Learning Representations (ICLR 2020), 2018 | 140 | 2018 |
| Revisiting resnets: Improved training and scaling strategies I Bello, W Fedus, X Du, ED Cubuk, A Srinivas, TY Lin, J Shlens, B Zoph Advances in Neural Information Processing Systems 34, 22614-22627, 2021 | 104 | 2021 |
| First dark matter search results from a surface run of the 10-L DMTPC directional dark matter detector S Ahlen, JBR Battat, T Caldwell, C Deaconu, D Dujmic, W Fedus, P Fisher, ... Physics Letters B 695 (1-4), 124-129, 2011 | 99 | 2011 |
| Palm: Scaling language modeling with pathways A Chowdhery, S Narang, J Devlin, M Bosma, G Mishra, A Roberts, ... arXiv preprint arXiv:2204.02311, 2022 | 94 | 2022 |
| Revisiting fundamentals of experience replay W Fedus, P Ramachandran, R Agarwal, Y Bengio, H Larochelle, ... International Conference on Machine Learning, 3061-3071, 2020 | 84 | 2020 |
| On bonus-based exploration methods in the arcade learning environment AA Taiga, W Fedus, MC Machado, A Courville, MG Bellemare arXiv preprint arXiv:2109.11052, 2021 | 61* | 2021 |
| Hyperbolic discounting and learning over multiple horizons W Fedus, C Gelada, Y Bengio, MG Bellemare, H Larochelle Reinforcement Learning and Decision Making (RLDM 2019), 2019 | 61 | 2019 |
| Recall Traces: Backtracking Models for Efficient Reinforcement Learning A Goyal, P Brakel, W Fedus, T Lillicrap, S Levine, H Larochelle, Y Bengio International Conference on Learning Representations (ICLR 2019), 2018 | 59 | 2018 |
| Disentangling the independently controllable factors of variation by interacting with the world V Thomas, E Bengio, W Fedus, J Pondard, P Beaudoin, H Larochelle, ... NIPS Workshop on Learning Disentangled Features (2017), 2017 | 50 | 2017 |
| Do transformer modifications transfer across implementations and applications? S Narang, HW Chung, Y Tay, W Fedus, T Fevry, M Matena, K Malkan, ... arXiv preprint arXiv:2102.11972, 2021 | 47* | 2021 |
| Glam: Efficient scaling of language models with mixture-of-experts N Du, Y Huang, AM Dai, S Tong, D Lepikhin, Y Xu, M Krikun, Y Zhou, ... International Conference on Machine Learning, 5547-5569, 2022 | 27 | 2022 |
| Algorithmic Improvements for Deep Reinforcement Learning applied to Interactive Fiction V Jain, W Fedus, H Larochelle, D Precup, MG Bellemare Association for the Advancement of Artificial Intelligence (AAAI 2020), 2019 | 26 | 2019 |
| Scale efficiently: Insights from pre-training and fine-tuning transformers Y Tay, M Dehghani, J Rao, W Fedus, S Abnar, HW Chung, S Narang, ... arXiv preprint arXiv:2109.10686, 2021 | 17 | 2021 |
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
