| 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 | 264 | 2019 |
| 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 | 73 | 2017 |
| 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 | 66 | 2018 |
| 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 | 56 | 2018 |
| Unsupervised meta-learning for reinforcement learning A Gupta, B Eysenbach, C Finn, S Levine arXiv preprint arXiv:1806.04640, 2018 | 51 | 2018 |
| Search on the replay buffer: Bridging planning and reinforcement learning B Eysenbach, RR Salakhutdinov, S Levine Advances in Neural Information Processing Systems, 15246-15257, 2019 | 50 | 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 | 41 | 2019 |
| 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 | 22 | 2019 |
| If maxent rl is the answer, what is the question? B Eysenbach, S Levine arXiv preprint arXiv:1910.01913, 2019 | 14 | 2019 |
| Learning to reach goals without reinforcement learning D Ghosh, A Gupta, J Fu, A Reddy, C Devin, B Eysenbach, S Levine arXiv preprint arXiv:1912.06088, 2019 | 8 | 2019 |
| Who is mistaken? B Eysenbach, C Vondrick, A Torralba arXiv preprint arXiv:1612.01175, 2016 | 5 | 2016 |
| Rewriting history with inverse rl: Hindsight inference for policy improvement B Eysenbach, X Geng, S Levine, R Salakhutdinov arXiv preprint arXiv:2002.11089, 2020 | 4 | 2020 |
| F-irl: Inverse reinforcement learning via state marginal matching T Ni, H Sikchi, Y Wang, T Gupta, L Lee, B Eysenbach arXiv preprint arXiv:2011.04709, 2020 | 2 | 2020 |
| 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 | 1 | 2020 |
| Weakly-Supervised Reinforcement Learning for Controllable Behavior L Lee, B Eysenbach, R Salakhutdinov, C Finn arXiv preprint arXiv:2004.02860, 2020 | 1 | 2020 |
| Learning to reach goals via iterated supervised learning D Ghosh, A Gupta, A Reddy, J Fu, C Devin, B Eysenbach, S Levine arXiv e-prints, arXiv: 1912.06088, 2019 | 1 | 2019 |
| Reinforcement learning with unknown reward functions B Eysenbach, J Tyo, S Gu, G Brain, R Salakhutdinov, Z Lipton, S Levine Task-Agnostic Reinforcement Learning Workshop at ICLR 2019, 2019 | 1 | 2019 |
| Model-Based Visual Planning with Self-Supervised Functional Distances S Tian, S Nair, F Ebert, S Dasari, B Eysenbach, C Finn, S Levine arXiv preprint arXiv:2012.15373, 2020 | | 2020 |
| ViNG: Learning Open-World Navigation with Visual Goals D Shah, B Eysenbach, G Kahn, N Rhinehart, S Levine arXiv preprint arXiv:2012.09812, 2020 | | 2020 |
| C-Learning: Learning to Achieve Goals via Recursive Classification B Eysenbach, R Salakhutdinov, S Levine arXiv preprint arXiv:2011.08909, 2020 | | 2020 |
Sergey LevineUC Berkeley, GoogleVerified email at eecs.berkeley.edu
