| Diversity Is All You Need: Learning Skills without a Reward Function B Eysenbach, A Gupta, J Ibarz, S Levine International Conference on Learning Representations, 2019 | 951 | 2019 |
| Search on the Replay Buffer: Bridging Planning and Reinforcement Learning B Eysenbach, R Salakhutdinov, S Levine Advances in Neural Information Processing Systems, 15246-15257, 2019 | 250 | 2019 |
| Efficient Exploration via State Marginal Matching L Lee, B Eysenbach, E Parisotto, E Xing, S Levine, R Salakhutdinov arXiv preprint arXiv:1906.05274, 2019 | 214 | 2019 |
| Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings JD Co-Reyes, YX Liu, A Gupta, B Eysenbach, P Abbeel, S Levine International Conference on Machine Learning, 2018 | 157 | 2018 |
| Clustervision: Visual Supervision of Unsupervised Clustering BC Kwon, B Eysenbach, J Verma, K Ng, C De Filippi, WF Stewart, A Perer IEEE transactions on visualization and computer graphics 24 (1), 142-151, 2017 | 147 | 2017 |
| Learning to Reach Goals via Iterated Supervised Learning D Ghosh, A Gupta, A Reddy, J Fu, C Devin, B Eysenbach, S Levine International Conference on Learning Representations, 2021 | 144* | 2021 |
| Leave No Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning B Eysenbach, S Gu, J Ibarz, S Levine International Conference on Learning Representations, 2018 | 139 | 2018 |
| Unsupervised Meta-Learning for Reinforcement Learning A Gupta, B Eysenbach, C Finn, S Levine arXiv preprint arXiv:1806.04640, 2018 | 131 | 2018 |
| RvS: What is Essential for Offline RL via Supervised Learning? S Emmons, B Eysenbach, I Kostrikov, S Levine International Conference on Learning Representations, 2022 | 116 | 2022 |
| Maximum Entropy RL (Provably) Solves Some Robust RL Problems B Eysenbach, S Levine International Conference on Learning Representations, 2022 | 111 | 2022 |
| Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills Y Chebotar, K Hausman, Y Lu, T Xiao, D Kalashnikov, J Varley, A Irpan, ... International Conference on Machine Learning, 2021 | 109 | 2021 |
| Learning to be Safe: Deep RL with a Safety Critic K Srinivasan, B Eysenbach, S Ha, J Tan, C Finn arXiv preprint arXiv:2010.14603, 2020 | 109 | 2020 |
| Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement B Eysenbach, X Geng, S Levine, R Salakhutdinov Advances in Neural Information Processing Systems 33, 2020 | 92 | 2020 |
| Unsupervised Curricula for Visual Meta-Reinforcement Learning A Jabri, K Hsu, A Gupta, B Eysenbach, S Levine, C Finn Advances in Neural Information Processing Systems, 2019 | 66 | 2019 |
| Recurrent Model-Free RL is a Strong Baseline for Many POMDPs T Ni, B Eysenbach, S Levine, R Salakhutdinov International Conference on Machine Learning, 2022 | 64* | 2022 |
| C-Learning: Learning to Achieve Goals via Recursive Classification B Eysenbach, R Salakhutdinov, S Levine International Conference on Learning Representations, 2021 | 58 | 2021 |
| Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers B Eysenbach, S Chaudhari, S Asawa, S Levine, R Salakhutdinov International Conference on Learning Representations, 2020 | 57 | 2020 |
| ViNG: Learning open-world navigation with visual goals D Shah, B Eysenbach, G Kahn, N Rhinehart, S Levine International Conference on Robotics and Automation, 13215-13222, 2021 | 55 | 2021 |
| Contrastive Learning as Goal-Conditioned Reinforcement Learning B Eysenbach, T Zhang, S Levine, RR Salakhutdinov Advances in Neural Information Processing Systems 35, 35603-35620, 2022 | 54 | 2022 |
| f-IRL: Inverse Reinforcement Learning via State Marginal Matching T Ni, H Sikchi, Y Wang, T Gupta, L Lee, B Eysenbach Conference on Robot Learning, 2020 | 54 | 2020 |
Sergey LevineUC Berkeley, GoogleVerified email at eecs.berkeley.edu
