| An actor-critic algorithm for sequence prediction D Bahdanau, P Brakel, K Xu, A Goyal, R Lowe, J Pineau, A Courville, ... ICLR'17, 2016 | 516 | 2016 |
| Professor forcing: A new algorithm for training recurrent networks A Goyal, A Lamb, Y Zhang, S Zhang, AC Courville, Y Bengio Advances In Neural Information Processing Systems, 4601-4609, 2016 | 475* | 2016 |
| Zoneout: Regularizing rnns by randomly preserving hidden activations D Krueger, T Maharaj, J Kramár, M Pezeshki, N Ballas, NR Ke, A Goyal, ... ICLR'17, 2016 | 303 | 2016 |
| Toward causal representation learning B Schölkopf, F Locatello, S Bauer, NR Ke, N Kalchbrenner, A Goyal, ... Proceedings of the IEEE 109 (5), 612-634, 2021 | 227 | 2021 |
| A meta-transfer objective for learning to disentangle causal mechanisms Y Bengio, T Deleu, N Rahaman, R Ke, S Lachapelle, O Bilaniuk, A Goyal, ... ICLR'20, 2019 | 197 | 2019 |
| Z-forcing: Training stochastic recurrent networks A Goyal, A Sordoni, MA Côté, NR Ke, Y Bengio Advances in neural information processing systems, 6713-6723, 2017 | 156* | 2017 |
| Recurrent independent mechanisms A Goyal, A Lamb, J Hoffmann, S Sodhani, S Levine, Y Bengio, ... arXiv preprint arXiv:1909.10893, 2019 | 152 | 2019 |
| InfoBot: Transfer and Exploration via the Information Bottleneck A Goyal, R Islam, D Strouse, Z Ahmed, M Botvinick, H Larochelle, ... ICLR'19, 2019 | 101 | 2019 |
| Inductive biases for deep learning of higher-level cognition A Goyal, Y Bengio arXiv preprint arXiv:2011.15091, 2020 | 92 | 2020 |
| Sparse Attentive Backtracking: Temporal credit assignment through reminding NR Ke, A Goyal, O Bilaniuk, J Binas, MC Mozer, C Pal, Y Bengio Advances in Neural Information Processing Systems, 7651-7662, 2018 | 84* | 2018 |
| Learning neural causal models from unknown interventions NR Ke, O Bilaniuk, A Goyal, S Bauer, H Larochelle, B Schölkopf, ... arXiv preprint arXiv:1910.01075, 2019 | 74 | 2019 |
| Maximum Entropy Generators for Energy-Based Models R Kumar, A Goyal, A Courville, Y Bengio arXiv preprint arXiv:1901.08508, 2019 | 69 | 2019 |
| Recall traces: Backtracking models for efficient reinforcement learning A Goyal, P Brakel, W Fedus, T Lillicrap, S Levine, H Larochelle, Y Bengio ICLR'19, 2018 | 51 | 2018 |
| Learning dynamics model in reinforcement learning by incorporating the long term future NR Ke, A Singh, A Touati, A Goyal, Y Bengio, D Parikh, D Batra ICLR'19, 2019 | 50* | 2019 |
| State-reification networks: Improving generalization by modeling the distribution of hidden representations A Lamb, J Binas, A Goyal, S Subramanian, I Mitliagkas, D Kazakov, ... ICML'19, arXiv preprint arXiv:1804.02485, 2019 | 47* | 2019 |
| Causalworld: A robotic manipulation benchmark for causal structure and transfer learning O Ahmed, F Träuble, A Goyal, A Neitz, Y Bengio, B Schölkopf, M Wüthrich, ... arXiv preprint arXiv:2010.04296, 2020 | 45 | 2020 |
| Variational walkback: Learning a transition operator as a stochastic recurrent net A Goyal, NR Ke, S Ganguli, Y Bengio Advances in Neural Information Processing Systems, 4392-4402, 2017 | 40* | 2017 |
| Extending the framework of equilibrium propagation to general dynamics B Scellier, A Goyal, J Binas, T Mesnard, Y Bengio | 32* | 2018 |
| Learning to combine top-down and bottom-up signals in recurrent neural networks with attention over modules S Mittal, A Lamb, A Goyal, V Voleti, M Shanahan, G Lajoie, M Mozer, ... International Conference on Machine Learning, 6972-6986, 2020 | 30 | 2020 |
| Small-gan: Speeding up gan training using core-sets S Sinha, H Zhang, A Goyal, Y Bengio, H Larochelle, A Odena International Conference on Machine Learning, 9005-9015, 2020 | 29 | 2020 |
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
