| Agile autonomous driving using end-to-end deep imitation learning Y Pan, CA Cheng, K Saigol, K Lee, X Yan, E Theodorou, B Boots arXiv preprint arXiv:1709.07174, 2017 | 386 | 2017 |
| Continuous-time Gaussian process motion planning via probabilistic inference M Mukadam, J Dong, X Yan, F Dellaert, B Boots The International Journal of Robotics Research 37 (11), 1319-1340, 2018 | 250 | 2018 |
| 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 | 176 | 2020 |
| Gaussian process motion planning M Mukadam, X Yan, B Boots 2016 IEEE international conference on robotics and automation (ICRA), 9-15, 2016 | 171 | 2016 |
| Fast policy learning through imitation and reinforcement CA Cheng, X Yan, N Wagener, B Boots arXiv preprint arXiv:1805.10413, 2018 | 97 | 2018 |
| Incremental sparse GP regression for continuous-time trajectory estimation and mapping X Yan, V Indelman, B Boots Robotics and Autonomous Systems 87, 120-132, 2017 | 50 | 2017 |
| Prediction under uncertainty in sparse spectrum Gaussian processes with applications to filtering and control Y Pan, X Yan, EA Theodorou, B Boots International Conference on Machine Learning, 2760-2768, 2017 | 48 | 2017 |
| Trajectory-wise control variates for variance reduction in policy gradient methods CA Cheng, X Yan, B Boots Conference on Robot Learning, 1379-1394, 2020 | 33 | 2020 |
| Predictor-corrector policy optimization CA Cheng, X Yan, N Ratliff, B Boots International Conference on Machine Learning, 1151-1161, 2019 | 26 | 2019 |
| Accelerating imitation learning with predictive models CA Cheng, X Yan, E Theodorou, B Boots The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 26 | 2019 |
| Tactile teacher: Sensing finger tapping in piano playing CP Hsiao, R Li, X Yan, EYL Do Proceedings of the Ninth International Conference on Tangible, Embedded, and …, 2015 | 22 | 2015 |
| Approximately optimal continuous-time motion planning and control via probabilistic inference M Mukadam, CA Cheng, X Yan, B Boots 2017 IEEE International Conference on Robotics and Automation (ICRA), 664-671, 2017 | 17 | 2017 |
| Learning deep neural network control policies for agile off-road autonomous driving Y Pan, CA Cheng, K Saigol, K Lee, X Yan, E Theodorou, B Boots The NIPS Deep Rienforcement Learning Symposium 134, 2017 | 11 | 2017 |
| Adaptive probabilistic trajectory optimization via efficient approximate inference Y Pan, X Yan, E Theodorou, B Boots arXiv preprint arXiv:1608.06235, 2016 | 9 | 2016 |
| Large-scale Gaussian process regression via doubly stochastic gradient descent X Yan, B Xie, L Song, B Boots, G EDU The ICML Workshop on Large-Scale Kernel Learning, 2015 | 7 | 2015 |
| Explaining fast improvement in online imitation learning X Yan, B Boots, CA Cheng Uncertainty in Artificial Intelligence, 1874-1884, 2021 | 6 | 2021 |
| Towards uniformly superhuman autonomy via subdominance minimization B Ziebart, S Choudhury, X Yan, P Vernaza International Conference on Machine Learning, 27654-27670, 2022 | 4 | 2022 |
| Scalable reinforcement learning via trajectory optimization and approximate Gaussian process regression Y Pan, X Yan, E Theodorou, B Boots NIPS Workshop on Advances in Approximate Bayesian Inference, 2015 | 4 | 2015 |
| Explaining fast improvement in online policy optimization X Yan, B Boots, CA Cheng Computing Research Repository, 2020 | 2 | 2020 |
| Solving the linear Bellman equation via dual kernel embeddings Y Pan, X Yan, B Dai, L Song, E Theodorou, B Boots Georgia Institute of Technology, Tech. Rep, 2017 | 2 | 2017 |
Byron BootsAssociate Professor, University of WashingtonVerified email at cs.washington.edu
