BeTAIL: Behavior Transformer Adversarial Imitation Learning from Human Racing Gameplay C Weaver, C Tang, C Hao, K Kawamoto, M Tomizuka, W Zhan arXiv preprint arXiv:2402.14194, 2024 | | 2024 |
Skill-Critic: Refining Learned Skills for Hierarchical Reinforcement Learning C Hao, C Weaver, C Tang, K Kawamoto, M Tomizuka, W Zhan IEEE Robotics and Automation Letters, 2024 | | 2024 |
Residual Q-Learning: Offline and Online Policy Customization without Value C Li, C Tang, H Nishimura, J Mercat, M Tomizuka, W Zhan Advances in Neural Information Processing Systems 36, 2024 | | 2024 |
Pessimistic offline reinforcement learning system and method M Huang, LI Jinning, C Tang, M Tomizuka, W Zhan US Patent App. 17/969,129, 2024 | | 2024 |
Learning Online Belief Prediction for Efficient POMDP Planning in Autonomous Driving Z Huang, C Tang, C Lv, M Tomizuka, W Zhan arXiv preprint arXiv:2401.15315, 2024 | | 2024 |
Active Exploration in Iterative Gaussian Process Regression for Uncertainty Modeling in Autonomous Racing T Benciolini, C Tang, M Leibold, C Weaver, M Tomizuka, W Zhan arXiv preprint arXiv:2311.01993, 2023 | | 2023 |
Quantifying Agent Interaction in Multi-agent Reinforcement Learning for Cost-efficient Generalization Y Chen, C Tang, R Tian, C Li, J Li, M Tomizuka, W Zhan arXiv preprint arXiv:2310.07218, 2023 | | 2023 |
Pre-training on synthetic driving data for trajectory prediction Y Li, SZ Zhao, C Xu, C Tang, C Li, M Ding, M Tomizuka, W Zhan arXiv preprint arXiv:2309.10121, 2023 | 3 | 2023 |
Guided online distillation: Promoting safe reinforcement learning by offline demonstration J Li, X Liu, B Zhu, J Jiao, M Tomizuka, C Tang, W Zhan arXiv preprint arXiv:2309.09408, 2023 | 4 | 2023 |
Editing Driver Character: Socially-Controllable Behavior Generation for Interactive Traffic Simulation WJ Chang, C Tang, C Li, Y Hu, M Tomizuka, W Zhan IEEE Robotics and Automation Letters, 2023 | 3 | 2023 |
Skill-critic: Refining learned skills for reinforcement learning C Hao, C Weaver, C Tang, K Kawamoto, M Tomizuka, W Zhan arXiv preprint arXiv:2306.08388, 2023 | 2 | 2023 |
Double-Iterative Gaussian Process Regression for Modeling Error Compensation in Autonomous Racing S Su, C Hao, C Weaver, C Tang, W Zhan, M Tomizuka IFAC-PapersOnLine 56 (2), 7940-7947, 2023 | 1 | 2023 |
Pretram: Self-supervised pre-training via connecting trajectory and map C Xu, T Li, C Tang, L Sun, K Keutzer, M Tomizuka, A Fathi, W Zhan European Conference on Computer Vision, 34-50, 2022 | 16 | 2022 |
Interventional behavior prediction: Avoiding overly confident anticipation in interactive prediction C Tang, W Zhan, M Tomizuka 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022 | 14 | 2022 |
Domain knowledge driven pseudo labels for interpretable goal-conditioned interactive trajectory prediction L Sur, C Tang, Y Niu, E Sachdeva, C Choi, T Misu, M Tomizuka, W Zhan 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022 | 16 | 2022 |
Hierarchical planning through goal-conditioned offline reinforcement learning J Li, C Tang, M Tomizuka, W Zhan IEEE Robotics and Automation Letters 7 (4), 10216-10223, 2022 | 42 | 2022 |
Dealing with the unknown: Pessimistic offline reinforcement learning J Li, C Tang, M Tomizuka, W Zhan Conference on Robot Learning, 1455-1464, 2022 | 15 | 2022 |
Outracing human racers with model-based autonomous racing C Hao, C Tang, E Bergkvist, C Weaver, L Sun, W Zhan, M Tomizuka arXiv preprint, 2022 | 3 | 2022 |
PreTraM: Self-Supervised Pre-training via Connecting Trajectory and Map Supplementary Material C Xu, T Li, C Tang, L Sun, K Keutzer, M Tomizuka, A Fathi, W Zhan European Conference on Computer Vision (ECCV), 2022 | 1 | 2022 |
Designing Explainable Autonomous Driving System for Trustworthy Interaction C Tang University of California, Berkeley, 2022 | 2 | 2022 |