| Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ... arXiv preprint arXiv:2312.11805, 2023 | 1611 | 2023 |
| 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 | 1273 | 2021 |
| 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 | 742* | 2016 |
| An actor-critic algorithm for sequence prediction D Bahdanau, P Brakel, K Xu, A Goyal, R Lowe, J Pineau, A Courville, ... ICLR'17, 2016 | 738 | 2016 |
| The llama 3 herd of models A Dubey, A Jauhri, A Pandey, A Kadian, A Al-Dahle, A Letman, A Mathur, ... arXiv preprint arXiv:2407.21783, 2024 | 435 | 2024 |
| 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 | 391 | 2016 |
| 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 | 388 | 2019 |
| Inductive biases for deep learning of higher-level cognition A Goyal, Y Bengio Proceedings of the Royal Society A 478 (2266), 20210068, 2022 | 386 | 2022 |
| Recurrent independent mechanisms A Goyal, A Lamb, J Hoffmann, S Sodhani, S Levine, Y Bengio, ... arXiv preprint arXiv:1909.10893, 2019 | 354 | 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 | 220* | 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 | 188 | 2019 |
| InfoBot: Transfer and Exploration via the Information Bottleneck A Goyal, R Islam, D Strouse, Z Ahmed, M Botvinick, H Larochelle, ... ICLR'19, 2019 | 170 | 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 | 133 | 2020 |
| On disentangled representations learned from correlated data F Träuble, E Creager, N Kilbertus, F Locatello, A Dittadi, A Goyal, ... International conference on machine learning, 10401-10412, 2021 | 126 | 2021 |
| 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 | 121* | 2018 |
| Maximum Entropy Generators for Energy-Based Models R Kumar, A Goyal, A Courville, Y Bengio arXiv preprint arXiv:1901.08508, 2019 | 119 | 2019 |
| 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 | 96 | 2021 |
| 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 | 90* | 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 | 87 | 2021 |
| 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 | 83 | 2020 |
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
