E-MAPP: Efficient Multi-Agent Reinforcement Learning with Parallel Program Guidance. - Can Chang; Ni Mu; Jiajun Wu 001; Ling Pan; Huazhe Xu (NeurIPS, 2022)

A semi-supervised classification RBM with an improved fMRI representation algorithm. - Can Chang; Ning Liu; Li Yao 002; Xiaojie Zhao (Comput. Methods Programs Biomed., 2022)

RL-ViGen: A Reinforcement Learning Benchmark for Visual Generalization. - Zhecheng Yuan; Sizhe Yang; Pu Hua; Can Chang; Kaizhe Hu; Huazhe Xu (NeurIPS, 2023)

RL-ViGen: A Reinforcement Learning Benchmark for Visual Generalization. - Zhecheng Yuan; Sizhe Yang; Pu Hua; Can Chang; Kaizhe Hu; Xiaolong Wang; Huazhe Xu (CoRR, 2023)

Online Control with Adversarial Disturbance for Continuous-time Linear Systems. - Jingwei Li; Jing Dong 008; Can Chang; Baoxiang Wang 001; Jingzhao Zhang (NeurIPS, 2024)

Looking Backward: Retrospective Backward Synthesis for Goal-Conditioned GFlowNets. - Haoran He; Can Chang; Huazhe Xu; Ling Pan (ICLR, 2025)

Enhancing Tumor Edge Consistency in Multimodal MRI Synthesis for Improved Glioma Segmentation. - Can Chang; Li Yao; Xiaojie Zhao (IEEE Signal Process. Lett., 2025)