Publications
Under Review
- H. Ce*, C. Weaver*, C. Tang, K. Kawamoto, M. Tomizuka, and W. Zhan, “Skill-critic: Refining learned skills for reinforcement learning,” under anonymous review
- C. Li*, C. Tang*, H. Nishimura, J. Mercat, M. Tomizuka, and W. Zhan, “Residual Q-learning: offline and online policy customization without value,” under anonymous review.
- C. Hao, C. Tang, E. Bergkvist, C. Weaver, L. Sun, W. Zhan, and M. Tomizuka, “Outracing human racers with model-based autonomous racing,” under revision for IEEE Transactions on Intelligent Vehicles (T-IV)
- C. Tang, N. Srishankar, S. Martin and M. Tomizuka, “Grounded relational inference: Domain knowledge-driven explainable autonomous driving,” under revision for IEEE Transactions on Intelligent Transportation System (T-ITS)
Journal
- W. Chang*, C. Tang*, C. Li, Y. Hu, M. Tomizuka, and W. Zhan, “Editing driver character: Socially-controllable behavior generation for interactive traffic simulation,” IEEE Robotics and Automation Letters (RA-L)
- J. Li, C. Tang, W. Zhan, and M. Tomizuka, “Hierarchical planning through goal-conditioned offline reinforcement learning,” IEEE Robotics and Automation Letters (RA-L) and IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022
- C. Tang*, Z. Xu* and M. Tomizuka, “Disturbance-observer-based tracking controller for neural network driving policy transfer,” IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2020
- Á. Cuenca, W. Zhan, J. Salt, J. Alcaina, C. Tang and M. Tomizuka, “A remote control strategy for an autonomous vehicle with slow sensor using kalman filtering and dual-rate control,” Sensors, 2019.
- X. Liu, C. Tang, X. Du, S. Xiong, S. Xi, Y. Liu, X. Shen, Q. Zheng, Z. Wang, Y. Wu, et al., “A highly sensitive graphene woven fabric strain sensor for wearable wireless musical instruments,” Materials Horizons, 2017
Conference Proceedings
- S. Su, C. Hao, C. Weaver, C. Tang, W. Zhan, and M. Tomizuka, “Double-iterative gaussian process regression for modeling error compensation in autonomous racing,” IFAC World Congress, 2023
- C. Xu*, T. Li*, C. Tang, L. Sun, K. Keutzer, M. Tomizuka, A. Fathi, and W. Zhan, “PreTraM: Self-supervised pre-training via connecting trajectory and map,” European Conference on Computer Vision (ECCV), 2022
- L. Sun*, C. Tang*, Y. Niu, E. Sachdeva, C. Choi, T. Misu, M. Tomizuka, and W. Zhan, “Domain knowledge driven pseudo labels for interpretable goal-conditioned interactive trajectory prediction,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022
- C. Tang, W. Zhan, and M. Tomizuka, “Interventional behavior prediction: Avoiding overly confident anticipation in interactive prediction,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022
- C. Tang, W. Zhan and M. Tomizuka, “Exploring social posterior collapse in variational autoencoder for interaction modeling,” Conference on Neural Information Processing Systems (NeurIPS), 2021
- J. Li, C. Tang, M. Tomizuka and W. Zhan, “Dealing with the unknonw: Pessimistic offline reinforcement learning,” Annual Conference on Robot Learning (CoRL), 2021
- J. M. Salt Ducaju, C. Tang, M. Tomizuka and C. -Y. Chan, “Application specific system identification for model-based control in self-driving cars,” IEEE Intelligent Vehicles Symposium (IV), 2020
- C. Tang, J. Chen and M. Tomizuka, “Adaptive probabilistic vehicle trajectory prediction through physically feasible bayesian recurrent neural network,” International Conference on Robotics and Automation (ICRA), 2019
- Z. Xu, H. Chang, C. Tang, C. Liu and M. Tomizuka, “Toward modularization of neural network autonomous driving policy using parallel attribute networks,” IEEE Intelligent Vehicles Symposium (IV), 2019
- Z. Xu*, C. Tang*, and M. Tomizuka, “Zero-shot deep reinforcement learning driving policy transfer for autonomous vehicles based on robust control,” International Conference on Intelligent Transportation Systems (ITSC), 2018 (Best Student Paper Runner-up)
- J. Chen, C. Tang, L. Xin, S. E. Li and M. Tomizuka, “Continuous decision making for on-road autonomous driving under uncertain and interactive environments,” IEEE Intelligent Vehicles Symposium (IV), 2018
- C. Zhao, R. Xu, K. Song, D. Liu, S. Ma, C. Tang, C. Liang, Y. Zohar, and Y.K. Lee, “The capillary number effect on the capture efficiency of cancer cells on composite microfluidic filtration chips”. IEEE International Conference on Micro Electro Mechanical Systems (MEMS), 2015.
Workshop
- W. Chang*, C. Tang*, C. Li, Y. Hu, M. Tomizuka, and W. Zhan, “Editing driver character: Socially-controllable behavior generation for interactive traffic simulation,” CVPR Workshop on Multi-Agent Behavior: Properties, Computation, and Emergence (MABe), 2023
- C. Tang, N. Srishankar, S. Martin and M. Tomizuka, “Explainable autonomous driving with grounded relational inference,” NeurIPS Workshop on Machine Learning for Autonomous Driving (ML4AD), 2020
The superscript * indicates equal contribution.