Spatio-temporal graph dual-attention network for multi-agent prediction and tracking J Li, H Ma, Z Zhang, J Li, M Tomizuka IEEE Transactions on Intelligent Transportation Systems 23 (8), 10556-10569, 2021 | 72 | 2021 |
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 | 40 | 2022 |
A safe hierarchical planning framework for complex driving scenarios based on reinforcement learning J Li, L Sun, J Chen, M Tomizuka, W Zhan 2021 IEEE International Conference on Robotics and Automation (ICRA), 2660-2666, 2021 | 34 | 2021 |
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 |
Interaction-aware behavior planning for autonomous vehicles validated with real traffic data J Li, L Sun, W Zhan, M Tomizuka Dynamic Systems and Control Conference 84287, V002T31A005, 2020 | 14 | 2020 |
A novel integrated SVM for fault diagnosis using KPCA and GA LI Jinning Journal of Physics: Conference Series 1207 (1), 012002, 2019 | 5 | 2019 |
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 |
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 |