| 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 | 500 | 2021 |
| Zoneout: Regularizing rnns by randomly preserving hidden activations D Krueger, T Maharaj, J Kramár, M Pezeshki, N Ballas, NR Ke, A Goyal, ... 5th International Conference on Learning Representations (ICLR 2017), 2016 | 333 | 2016 |
| A deep reinforcement learning chatbot IV Serban, C Sankar, M Germain, S Zhang, Z Lin, S Subramanian, T Kim, ... Alexa challenge 2017, 2017 | 285 | 2017 |
| A meta-transfer objective for learning to disentangle causal mechanisms Y Bengio, T Deleu, N Rahaman, R Ke, S Lachapelle, O Bilaniuk, A Goyal, ... 8th International Conference on Learning Representations (ICLR 2020), 2019 | 268 | 2019 |
| Z-Forcing: Training stochastic recurrent networks AGAP GOYAL, A Sordoni, MA Côté, N Ke, Y Bengio 31th Annual Conference on Neural Information Processing Systems (NIPS 2017 …, 2017 | 183* | 2017 |
| 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 | 122 | 2019 |
| Ethical challenges in data-driven dialogue systems P Henderson, K Sinha, N Angelard-Gontier, NR Ke, G Fried, R Lowe, ... Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 123-129, 2018 | 114 | 2018 |
| Cascading bandits for large-scale recommendation problems S Zong, H Ni, K Sung, NR Ke, Z Wen, B Kveton 32nd Conference on Uncertainty in Artificial Intelligence 2016, UAI 2016, 2016 | 97 | 2016 |
| Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding NR Ke, A Goyal, O Bilaniuk, J Binas, MC Mozer, C Pal, Y Bengio 32nd Conference on Neural Information Processing Systems (NIPS 2018 …, 2018 | 92* | 2018 |
| Transferring knowledge from a RNN to a DNN W Chan, NR Ke, I Lane 16th Annual Conference of the International Speech Communication Association …, 2015 | 91 | 2015 |
| Twin networks: Matching the future for sequence generation D Serdyuk*, NR Ke*, A Sordoni, A Trischler, C Pal, Y Bengio 6th International Conference on Learning Representations (ICLR 2018), 2018 | 69* | 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 7th International Conference on Learning Representations (ICLR 2019), 2019 | 63* | 2019 |
| Neural production systems AG ALIAS PARTH GOYAL, A Didolkar, NR Ke, C Blundell, P Beaudoin, ... Advances in Neural Information Processing Systems 34, 25673-25687, 2021 | 48* | 2021 |
| Coordination among neural modules through a shared global workspace A Goyal, A Didolkar, A Lamb, K Badola, NR Ke, N Rahaman, J Binas, ... arXiv preprint arXiv:2103.01197, 2021 | 48 | 2021 |
| Variational walkback: Learning a transition operator as a stochastic recurrent net AGAP Goyal, N Ke, S Ganguli, Y Bengio 31th Annual Conference on Neural Information Processing Systems (NIPS 2017 …, 2017 | 48* | 2017 |
| h-detach: Modifying the LSTM Gradient Towards Better Optimization B Kanuparthi, D Arpit, G Kerg, NR Ke, I Mitliagkas, Y Bengio 7th International Conference on Learning Representations (ICLR 2019), 2018 | 36* | 2018 |
| A deep reinforcement learning chatbot (short version) IV Serban, C Sankar, M Germain, S Zhang, Z Lin, S Subramanian, T Kim, ... arXiv preprint arXiv:1801.06700, 2018 | 33* | 2018 |
| Task loss estimation for sequence prediction D Bahdanau, D Serdyuk, P Brakel, NR Ke, J Chorowski, A Courville, ... arXiv preprint arXiv:1511.06456, 2015 | 32 | 2015 |
| Focused hierarchical RNNs for conditional sequence processing N Rosemary Ke, K Żołna, A Sordoni, Z Lin, A Trischler, Y Bengio, ... Proceedings of Machine Learning Research 80, 2018 | 25* | 2018 |
| ICLR reproducibility challenge 2019 J Pineau, K Sinha, G Fried, RN Ke, H Larochelle ReScience C 5 (2), 5, 2019 | 24* | 2019 |
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
