| Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ... arXiv preprint arXiv:2312.11805, 2023 | 3308 | 2023 |
| Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context G Team, P Georgiev, VI Lei, R Burnell, L Bai, A Gulati, G Tanzer, ... arXiv preprint arXiv:2403.05530, 2024 | 1234 | 2024 |
| Data-Efficient Reinforcement Learning with Self-Predictive Representations M Schwarzer*, A Anand*, R Goel, RD Hjelm, A Courville, P Bachman ICLR 2021, 2020 | 396 | 2020 |
| Unsupervised State Representation Learning in Atari A Anand, E Racah, S Ozair, Y Bengio, MA Côté, RD Hjelm NeurIPS 2019, 2019 | 318 | 2019 |
| We used neural networks to detect clickbaits: You won’t believe what happened next! A Anand, T Chakraborty, N Park European Conference on Information Retrieval, 541-547, 2017 | 173 | 2017 |
| Pretraining Representations for Data-Efficient Reinforcement Learning M Schwarzer, N Rajkumar, M Noukhovitch, A Anand, L Charlin, D Hjelm, ... NeurIPS 2021, 2021 | 158 | 2021 |
| HoME: A household multimodal environment S Brodeur, E Perez, A Anand, F Golemo, L Celotti, F Strub, J Rouat, ... International Conference on Learning Representations (ICLR) Workshop Track, 2018 | 136 | 2018 |
| Many-shot in-context learning R Agarwal, A Singh, L Zhang, B Bohnet, L Rosias, S Chan, B Zhang, ... Advances in Neural Information Processing Systems 37, 76930-76966, 2025 | 101 | 2025 |
| Beyond human data: Scaling self-training for problem-solving with language models A Singh, JD Co-Reyes, R Agarwal, A Anand, P Patil, X Garcia, PJ Liu, ... arXiv preprint arXiv:2312.06585, 2023 | 100 | 2023 |
| Blindfold Baselines for Embodied QA A Anand, E Belilovsky, K Kastner, H Larochelle, A Courville arXiv preprint arXiv:1811.05013, 2018 | 51 | 2018 |
| Procedural Generalization by Planning with Self-Supervised World Models A Anand, J Walker, Y Li, E Vértes, J Schrittwieser, S Ozair, T Weber, ... ICLR 2022, 2021 | 37 | 2021 |
| MMGAN: manifold-matching generative adversarial networks N Park, A Anand, JRA Moniz, K Lee, J Choo, DK Park, T Chakraborty, ... 2018 24th international conference on pattern recognition (ICPR), 1343-1348, 2018 | 19 | 2018 |
| Contrastive self-supervised learning A Anand https://ankeshanand.com/blog/2020/01/26/contrative-self-supervised-learning.html, 2020 | 16* | 2020 |
| FairScholar: balancing relevance and diversity for scientific paper recommendation A Anand, T Chakraborty, A Das European conference on information retrieval, 753-757, 2017 | 12 | 2017 |
| Investigating the role of model-based learning in exploration and transfer JC Walker, E Vértes, Y Li, G Dulac-Arnold, A Anand, T Weber, JB Hamrick International Conference on Machine Learning, 35368-35383, 2023 | 7 | 2023 |
| Self-supervision for reinforcement learning A Anand | | 2024 |
Aaron CourvilleProfessor, DIRO, Université de Montréal, Mila, Cifar CAI chairПотвърден имейл адрес: umontreal.ca