NADPEx: An on-policy temporally consistent exploration method for deep reinforcement learning. - Sirui Xie; Junning Huang; Lanxin Lei; Chunxiao Liu; Zheng Ma 008; Wei Zhang 114; Liang Lin (ICLR (Poster), 2019)

Biased Estimates of Advantages over Path Ensembles. - Lanxin Lei; Zhizhong Li 002; Dahua Lin (CoRR, 2019)

The NEOLIX Open Dataset for AutonomousDriving. - Lichao Wang; Lanxin Lei; Hongli Song; Weibao Wang (CoRR, 2020)

KB-Tree: Learnable and Continuous Monte-Carlo Tree Search for Autonomous Driving Planning. - Lanxin Lei; Ruiming Luo; Renjie Zheng; Jingke Wang; Jianwei Zhang; Cong Qiu; Liulong Ma; Liyang Jin; Ping Zhang; Junbo Chen (IROS, 2021)

Cola-HRL: Continuous-Lattice Hierarchical Reinforcement Learning for Autonomous Driving. - Lingping Gao; Ziqing Gu; Cong Qiu; Lanxin Lei; Shengbo Eben Li; Sifa Zheng; Wei Jing; Junbo Chen (IROS, 2022)

Learning to Model Diverse Driving Behaviors in Highly Interactive Autonomous Driving Scenarios with Multi-Agent Reinforcement Learning. - Weiwei Liu; Wenxuan Hu; Wei Jing; Lanxin Lei; Lingping Gao; Yong Liu 007 (CoRR, 2024)

Learning to Model Diverse Driving Behaviors in Highly Interactive Autonomous Driving Scenarios With Multiagent Reinforcement Learning. - Weiwei Liu; Wenxuan Hu; Wei Jing; Lanxin Lei; Lingping Gao; Yong Liu 007 (IEEE Syst. J., 2025)