Acme: A research framework for distributed reinforcement learning MW Hoffman, B Shahriari, J Aslanides, G Barth-Maron, N Momchev, ... arXiv preprint arXiv:2006.00979, 2020 | 227 | 2020 |
What matters in on-policy reinforcement learning? a large-scale empirical study M Andrychowicz, A Raichuk, P Stańczyk, M Orsini, S Girgin, R Marinier, ... arXiv preprint arXiv:2006.05990, 2020 | 187 | 2020 |
What matters for on-policy deep actor-critic methods? a large-scale study M Andrychowicz, A Raichuk, P Stańczyk, M Orsini, S Girgin, R Marinier, ... International conference on learning representations, 2020 | 144 | 2020 |
What matters for adversarial imitation learning? M Orsini, A Raichuk, L Hussenot, D Vincent, R Dadashi, S Girgin, M Geist, ... Advances in Neural Information Processing Systems 34, 14656-14668, 2021 | 64 | 2021 |
What matters in on-policy reinforcement learning M Andrychowicz, A Raichuk, P Stanczyk, M Orsini, S Girgin, R Marinier, ... A large-scale empirical study. CoRR, abs/2006.05990 3, 2020 | 29 | 2020 |
Hyperparameter selection for imitation learning L Hussenot, M Andrychowicz, D Vincent, R Dadashi, A Raichuk, S Ramos, ... International Conference on Machine Learning, 4511-4522, 2021 | 16 | 2021 |
What matters in on-policy reinforcement learning? a large-scale empirical study (2020) M Andrychowicz, A Raichuk, P Stanczyk, M Orsini, S Girgin, R Marinier, ... arXiv preprint arXiv:2006.05990, 2006 | 2 | 2006 |
On the importance of data collection for training general goal-reaching policies A Jacq, M Orsini, G Dulac-Arnold, O Pietquin, M Geist, O Bachem arXiv preprint arXiv:2211.03521, 2022 | 1 | 2022 |
C3PO: Learning to Achieve Arbitrary Goals via Massively Entropic Pretraining AD Jacq, M Orsini, G Dulac-Arnold, O Pietquin, M Geist, O Bachem | 1 | 2022 |