Lin, Haohong

9 publications

ICML 2025 A Generalizable Physics-Enhanced State Space Model for Long-Term Dynamics Forecasting in Complex Environments Yuchen Wang, Hongjue Zhao, Haohong Lin, Enze Xu, Lifang He, Huajie Shao

CVPR 2025 Causal Composition Diffusion Model for Closed-Loop Traffic Generation Haohong Lin, Xin Huang, Tung Phan, David Hayden, Huan Zhang, Ding Zhao, Siddhartha Srinivasa, Eric Wolff, Hongge Chen

NeurIPS 2025 Model-Based Policy Adaptation for Closed-Loop End-to-End Autonomous Driving Haohong Lin, Yunzhi Zhang, Wenhao Ding, Jiajun Wu, Ding Zhao

NeurIPS 2024 BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-Based Reinforcement Learning Haohong Lin, Wenhao Ding, Jian Chen, Laixi Shi, Jiacheng Zhu, Bo Li, Ding Zhao

DMLR 2024 Datasets and Benchmarks for Offline Safe Reinforcement Learning Zuxin Liu, Zijian Guo, Haohong Lin, Yihang Yao, Jiacheng Zhu, Zhepeng Cen, Hanjiang Hu, Wenhao Yu, Tingnan Zhang, Jie Tan, Ding Zhao

NeurIPS 2024 OASIS: Conditional Distribution Shaping for Offline Safe Reinforcement Learning Yihang Yao, Zhepeng Cen, Wenhao Ding, Haohong Lin, Shiqi Liu, Tingnan Zhang, Wenhao Yu, Ding Zhao

CoRL 2022 CausalAF: Causal Autoregressive Flow for Safety-Critical Driving Scenario Generation Wenhao Ding, Haohong Lin, Bo Li, Ding Zhao

NeurIPS 2022 Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning Wenhao Ding, Haohong Lin, Bo Li, Ding Zhao

CVPR 2022 Rethinking Controllable Variational Autoencoders Huajie Shao, Yifei Yang, Haohong Lin, Longzhong Lin, Yizhuo Chen, Qinmin Yang, Han Zhao