| The primacy bias in deep reinforcement learning E Nikishin, M Schwarzer, P D’Oro, PL Bacon, A Courville International conference on machine learning, 16828-16847, 2022 | 135 | 2022 |
| Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier P D'Oro, M Schwarzer, E Nikishin, PL Bacon, MG Bellemare, A Courville International Conference on Learning Representations (ICLR), 𝐍𝐨𝐭𝐚𝐛𝐥𝐞-𝐭𝐨𝐩-𝟓%, 2023 | 66 | 2023 |
| Improving stability in deep reinforcement learning with weight averaging E Nikishin, P Izmailov, B Athiwaratkun, D Podoprikhin, T Garipov, ... Uncertainty in artificial intelligence workshop on uncertainty in Deep learning, 2018 | 52 | 2018 |
| Understanding plasticity in neural networks C Lyle, Z Zheng, E Nikishin, BA Pires, R Pascanu, W Dabney International conference on machine learning, 2023 | 49 | 2023 |
| Control-oriented model-based reinforcement learning with implicit differentiation E Nikishin, R Abachi, R Agarwal, PL Bacon Proceedings of the AAAI Conference on Artificial Intelligence 36 (7), 7886-7894, 2022 | 34 | 2022 |
| Deep Reinforcement Learning with Plasticity Injection E Nikishin, J Oh, G Ostrovski, C Lyle, R Pascanu, W Dabney, A Barreto Advances in Neural Information Processing Systems 36, 2023 | 22 | 2023 |
| The Curse of Diversity in Ensemble-Based Exploration Z Lin, P D'Oro, E Nikishin, A Courville arXiv preprint arXiv:2405.04342, 2024 | | 2024 |
| Maxwell's Demon at Work: Efficient Pruning by Leveraging Saturation of Neurons S Dufort-Labbé, P D'Oro, E Nikishin, R Pascanu, PL Bacon, A Baratin arXiv preprint arXiv:2403.07688, 2024 | | 2024 |
| Quantifying and Understanding Adversarial Examples in Discrete Input Spaces V Kuleshov, E Nikishin, S Thakoor, T Lau, S Ermon arXiv preprint arXiv:2112.06276, 2021 | | 2021 |
| Unsupervised Domain Adaptation with Shared Latent Dynamics for Reinforcement Learning E Nikishin, A Ashukha, D Vetrov Bayesian Deep Learning Workshop on Neural Information Processing Systems, 5, 2019 | | 2019 |
| Unleashing The Potential of Data Sharing in Ensemble Deep Reinforcement Learning Z Lin, P D'Oro, E Nikishin, A Courville Deep Reinforcement Learning Workshop NeurIPS 2022, 0 | | |
Pierre-Luc BaconUniversity of Montreal在 mila.quebec 的电子邮件经过验证
