| Denoising diffusion probabilistic models J Ho, A Jain, P Abbeel Advances in neural information processing systems 33, 6840-6851, 2020 | 15667 | 2020 |
| Model-agnostic meta-learning for fast adaptation of deep networks C Finn, P Abbeel, S Levine International conference on machine learning, 1126-1135, 2017 | 14096 | 2017 |
| Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor T Haarnoja, A Zhou, P Abbeel, S Levine International conference on machine learning, 1861-1870, 2018 | 9794 | 2018 |
| Trust Region Policy Optimization J Schulman, S Levine, P Moritz, MI Jordan, P Abbeel International Conference on Machine Learning (ICML), 2015 | 8968 | 2015 |
| Infogan: Interpretable representation learning by information maximizing generative adversarial nets X Chen, Y Duan, R Houthooft, J Schulman, I Sutskever, P Abbeel Advances in neural information processing systems 29, 2016 | 5632 | 2016 |
| Multi-agent actor-critic for mixed cooperative-competitive environments R Lowe, YI Wu, A Tamar, J Harb, OAI Pieter Abbeel, I Mordatch Advances in neural information processing systems 30, 2017 | 5513 | 2017 |
| Apprenticeship learning via inverse reinforcement learning P Abbeel, AY Ng Proceedings of the twenty-first international conference on Machine learning, 1, 2004 | 4432 | 2004 |
| End-to-end training of deep visuomotor policies S Levine, C Finn, T Darrell, P Abbeel Journal of Machine Learning Research 17 (39), 1-40, 2016 | 4180 | 2016 |
| High-dimensional continuous control using generalized advantage estimation J Schulman, P Moritz, S Levine, M Jordan, P Abbeel arXiv preprint arXiv:1506.02438, 2015 | 4083 | 2015 |
| Domain randomization for transferring deep neural networks from simulation to the real world J Tobin, R Fong, A Ray, J Schneider, W Zaremba, P Abbeel 2017 IEEE/RSJ international conference on intelligent robots and systems …, 2017 | 3516 | 2017 |
| Soft actor-critic algorithms and applications T Haarnoja, A Zhou, K Hartikainen, G Tucker, S Ha, J Tan, V Kumar, ... arXiv preprint arXiv:1812.05905, 2018 | 3025 | 2018 |
| Hindsight experience replay M Andrychowicz, F Wolski, A Ray, J Schneider, R Fong, P Welinder, ... Advances in neural information processing systems 30, 2017 | 3013 | 2017 |
| Benchmarking deep reinforcement learning for continuous control Y Duan, X Chen, R Houthooft, J Schulman, P Abbeel International conference on machine learning, 1329-1338, 2016 | 2135 | 2016 |
| Decision transformer: Reinforcement learning via sequence modeling L Chen, K Lu, A Rajeswaran, K Lee, A Grover, M Laskin, P Abbeel, ... Advances in neural information processing systems 34, 15084-15097, 2021 | 1652 | 2021 |
| Sim-to-real transfer of robotic control with dynamics randomization XB Peng, M Andrychowicz, W Zaremba, P Abbeel 2018 IEEE international conference on robotics and automation (ICRA), 3803-3810, 2018 | 1650 | 2018 |
| Constrained policy optimization J Achiam, D Held, A Tamar, P Abbeel International conference on machine learning, 22-31, 2017 | 1608 | 2017 |
| A simple neural attentive meta-learner N Mishra, M Rohaninejad, X Chen, P Abbeel arXiv preprint arXiv:1707.03141, 2017 | 1589 | 2017 |
| Reinforcement learning with deep energy-based policies T Haarnoja, H Tang, P Abbeel, S Levine International conference on machine learning, 1352-1361, 2017 | 1539 | 2017 |
| Bottleneck transformers for visual recognition A Srinivas, TY Lin, N Parmar, J Shlens, P Abbeel, A Vaswani Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 1304 | 2021 |
| Deepmimic: Example-guided deep reinforcement learning of physics-based character skills XB Peng, P Abbeel, S Levine, M Van de Panne ACM Transactions On Graphics (TOG) 37 (4), 1-14, 2018 | 1215 | 2018 |
Sergey LevineUC Berkeley, Physical Intelligence在 eecs.berkeley.edu 的电子邮件经过验证
