| Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization K Ahuja, E Caballero, D Zhang, JC Gagnon-Audet, Y Bengio, I Mitliagkas, ... Advances in Neural Information Processing Systems 34, 2021 | 261 | 2021 |
| Sand-mask: An enhanced gradient masking strategy for the discovery of invariances in domain generalization S Shahtalebi, JC Gagnon-Audet, T Laleh, M Faramarzi, K Ahuja, I Rish arXiv preprint arXiv:2106.02266, 2021 | 53 | 2021 |
| Generative models of brain dynamics M Ramezanian-Panahi, G Abrevaya, JC Gagnon-Audet, V Voleti, I Rish, ... Frontiers in artificial intelligence 5, 807406, 2022 | 42* | 2022 |
| WOODS: Benchmarks for out-of-distribution generalization in time series JC Gagnon-Audet, K Ahuja, MJ Darvishi-Bayazi, P Mousavi, G Dumas, ... arXiv preprint arXiv:2203.09978, 2022 | 38 | 2022 |
| Learning brain dynamics with coupled low-dimensional nonlinear oscillators and deep recurrent networks G Abrevaya, G Dumas, AY Aravkin, P Zheng, JC Gagnon-Audet, ... Neural Computation 33 (8), 2087-2127, 2021 | 9 | 2021 |
| AWE: Adaptive weight-space ensembling for few-shot fine-tuning JC Gagnon-Audet, RP Monti, DJ Schwab ICLR 2023 Workshop on Mathematical and Empirical Understanding of Foundation …, 2023 | 4 | 2023 |
| Effective Latent Differential Equation Models via Attention and Multiple Shooting G Abrevaya, M Ramezanian-Panahi, JC Gagnon-Audet, I Rish, ... The Symbiosis of Deep Learning and Differential Equations III, 2023 | 2 | 2023 |
| GOKU-UI: Ubiquitous Inference through Attention and Multiple Shooting for Continuous-time Generative Models G Abrevaya, M Ramezanian-Panahi, JC Gagnon-Audet, I Rish, ... arXiv preprint arXiv:2307.05735, 2023 | 1 | 2023 |
Irina RishUniversity of Montreal / Mila -Quebec AI InstituteE-mail confirmado em mila.quebec