| Agile autonomous driving using end-to-end deep imitation learning Y Pan, CA Cheng, K Saigol, K Lee, X Yan, E Theodorou, B Boots Robotics: science and systems, 2018 | 430 | 2018 |
| Bellman-consistent pessimism for offline reinforcement learning T Xie, CA Cheng, N Jiang, P Mineiro, A Agarwal Advances in neural information processing systems 34, 6683-6694, 2021 | 371 | 2021 |
| Truncated back-propagation for bilevel optimization A Shaban, CA Cheng, N Hatch, B Boots The 22nd international conference on artificial intelligence and statistics …, 2019 | 367 | 2019 |
| Imitation learning for agile autonomous driving Y Pan, CA Cheng, K Saigol, K Lee, X Yan, EA Theodorou, B Boots The International Journal of Robotics Research 39 (2-3), 286-302, 2020 | 205 | 2020 |
| Adversarially trained actor critic for offline reinforcement learning CA Cheng, T Xie, N Jiang, A Agarwal International Conference on Machine Learning, 3852-3878, 2022 | 188 | 2022 |
| Direct nash optimization: Teaching language models to self-improve with general preferences C Rosset, CA Cheng, A Mitra, M Santacroce, A Awadallah, T Xie arXiv preprint arXiv:2404.03715, 2024 | 163 | 2024 |
| RMPflow: A Computational Graph for Automatic Motion Policy Generation CA Cheng, M Mukadam, J Issac, S Birchfield, D Fox, B Boots, N Ratliff International Workshop on the Algorithmic Foundations of Robotics, 441-457, 2018 | 113 | 2018 |
| Heuristic-guided reinforcement learning CA Cheng, A Kolobov, A Swaminathan Advances in Neural Information Processing Systems 34, 13550-13563, 2021 | 111 | 2021 |
| Variational inference for Gaussian process models with linear complexity CA Cheng, B Boots Advances in Neural Information Processing Systems 30, 2017 | 108 | 2017 |
| An online learning approach to model predictive control N Wagener, CA Cheng, J Sacks, B Boots arXiv preprint arXiv:1902.08967, 2019 | 104 | 2019 |
| Fast policy learning through imitation and reinforcement CA Cheng, X Yan, N Wagener, B Boots arXiv preprint arXiv:1805.10413, 2018 | 104 | 2018 |
| Intra order-preserving functions for calibration of multi-class neural networks A Rahimi, A Shaban, CA Cheng, R Hartley, B Boots Advances in neural information processing systems 33, 13456-13467, 2020 | 100 | 2020 |
| Safe reinforcement learning using advantage-based intervention NC Wagener, B Boots, CA Cheng International Conference on Machine Learning, 10630-10640, 2021 | 83 | 2021 |
| Cautiously optimistic policy optimization and exploration with linear function approximation A Zanette, CA Cheng, A Agarwal Conference on Learning Theory, 4473-4525, 2021 | 70 | 2021 |
| Orthogonally decoupled variational Gaussian processes H Salimbeni, CA Cheng, B Boots, M Deisenroth Advances in neural information processing systems 31, 2018 | 64 | 2018 |
| Adversarial model for offline reinforcement learning M Bhardwaj, T Xie, B Boots, N Jiang, CA Cheng Advances in Neural Information Processing Systems 36, 1245-1269, 2023 | 61* | 2023 |
| Incremental variational sparse Gaussian process regression CA Cheng, B Boots Advances in Neural Information Processing Systems 29, 2016 | 58 | 2016 |
| RMPflow: A Geometric Framework for Generation of Multitask Motion Policies CA Cheng, M Mukadam, J Issac, S Birchfield, D Fox, B Boots, N Ratliff IEEE Transactions on Automation Science and Engineering 18 (3), 968-987, 2021 | 54 | 2021 |
| Policy improvement via imitation of multiple oracles CA Cheng, A Kolobov, A Agarwal Advances in Neural Information Processing Systems 33, 5587-5598, 2020 | 52 | 2020 |
| Virtual impedance control for safe human-robot interaction SY Lo, CA Cheng, HP Huang Journal of Intelligent & Robotic Systems 82 (1), 3-19, 2016 | 46 | 2016 |
Byron BootsAssociate Professor, University of WashingtonVerified email at cs.washington.edu
