| One-shot imitation learning Y Duan, M Andrychowicz, B Stadie, OAI Jonathan Ho, J Schneider, ... Advances in neural information processing systems 30, 2017 | 822 | 2017 |
| Incentivizing exploration in reinforcement learning with deep predictive models BC Stadie, S Levine, P Abbeel arXiv preprint arXiv:1507.00814, 2015 | 561 | 2015 |
| Evolved policy gradients R Houthooft, Y Chen, P Isola, B Stadie, F Wolski, OAI Jonathan Ho, ... Advances in Neural Information Processing Systems 31, 2018 | 291 | 2018 |
| Third-person imitation learning BC Stadie, P Abbeel, I Sutskever arXiv preprint arXiv:1703.01703, 2017 | 275 | 2017 |
| Maximum entropy gain exploration for long horizon multi-goal reinforcement learning S Pitis, H Chan, S Zhao, B Stadie, J Ba International Conference on Machine Learning, 7750-7761, 2020 | 138 | 2020 |
| Some considerations on learning to explore via meta-reinforcement learning BC Stadie, G Yang, R Houthooft, X Chen, Y Duan, Y Wu, P Abbeel, ... arXiv preprint arXiv:1803.01118, 2018 | 137 | 2018 |
| World model as a graph: Learning latent landmarks for planning L Zhang, G Yang, BC Stadie International conference on machine learning, 12611-12620, 2021 | 84 | 2021 |
| One-shot pruning of recurrent neural networks by jacobian spectrum evaluation MS Zhang, B Stadie arXiv preprint arXiv:1912.00120, 2019 | 43 | 2019 |
| Transfer learning for estimating causal effects using neural networks SR Künzel, BC Stadie, N Vemuri, V Ramakrishnan, JS Sekhon, P Abbeel arXiv preprint arXiv:1808.07804, 2018 | 37 | 2018 |
| The importance of sampling inmeta-reinforcement learning B Stadie, G Yang, R Houthooft, P Chen, Y Duan, Y Wu, P Abbeel, ... Advances in Neural Information Processing Systems 31, 9280-9290, 2018 | 37 | 2018 |
| Learning intrinsic rewards as a bi-level optimization problem B Stadie, L Zhang, J Ba Conference on Uncertainty in Artificial Intelligence, 111-120, 2020 | 22 | 2020 |
| To the noise and back: Diffusion for shared autonomy T Yoneda, L Sun, B Stadie, M Walter arXiv preprint arXiv:2302.12244, 2023 | 17 | 2023 |
| Invariance through latent alignment T Yoneda, G Yang, MR Walter, B Stadie arXiv preprint arXiv:2112.08526, 2021 | 12* | 2021 |
| Cold diffusion on the replay buffer: Learning to plan from known good states Z Wang, T Oba, T Yoneda, R Shen, M Walter, BC Stadie Conference on Robot Learning, 3277-3291, 2023 | 5 | 2023 |
| Estimating heterogeneous treatment effects using neural networks with the Y-Learner BC Stadie, SR Künzel, N Vemuri, JS Sekhon | 4 | 2018 |
| Solving Robotics Problems in Zero-Shot with Vision-Language Models Z Wang, R Shen, B Stadie arXiv preprint arXiv:2407.19094, 2024 | 3 | 2024 |
| One demonstration imitation learning BC Stadie, S Zhao, Q Xu, B Li, L Zhang Advances in neural information processing systems 30, 2019 | 1 | 2019 |
| Simulating the stochastic dynamics and cascade failure of power networks C Matthews, B Stadie, J Weare, M Anitescu, C Demarco arXiv preprint arXiv:1806.02420, 2018 | 1 | 2018 |
| Learning as a Sampling Problem BC Stadie UC Berkeley, 2018 | 1 | 2018 |
| Understanding Hindsight Goal Relabeling from a Divergence Minimization Perspective L Zhang, BC Stadie arXiv preprint arXiv:2209.13046, 2022 | | 2022 |
Pieter AbbeelUC Berkeley | CovariantVerified email at cs.berkeley.edu
