Transformer: A New Paradigm for Building Data-Parallel Programming Models. - Peng Wang 028; Dan Meng 002; Jizhong Han; Jianfeng Zhan; Bibo Tu; Xiaofeng Shi; Le Wan (IEEE Micro, 2010)

Novel Standardized Representation Methods for Modular Service Robots. - Yibo Zou; Yusheng Ju; Zhenzhou Shao; Yefei Gong; Bo Sun; Le Wan; Tuo Shi (Int. J. Soc. Robotics, 2022)

Uncertainty-Driven Trajectory Truncation for Data Augmentation in Offline Reinforcement Learning. - Junjie Zhang; Jiafei Lyu; Xiaoteng Ma; Jiangpeng Yan; Jun Yang 028; Le Wan; Xiu Li 001 (ECAI, 2023)

State Advantage Weighting for Offline RL. - Jiafei Lyu; Aicheng Gong; Le Wan; Zongqing Lu 002; Xiu Li 001 (Tiny Papers @ ICLR, 2023)

Uncertainty-driven Trajectory Truncation for Model-based Offline Reinforcement Learning. - Junjie Zhang; Jiafei Lyu; Xiaoteng Ma; Jiangpeng Yan; Jun Yang 028; Le Wan; Xiu Li 001 (CoRR, 2023)

Towards Understanding How to Reduce Generalization Gap in Visual Reinforcement Learning. - Jiafei Lyu; Le Wan; Xiu Li 001; Zongqing Lu 002 (AAMAS, 2024)

SEABO: A Simple Search-Based Method for Offline Imitation Learning. - Jiafei Lyu; Xiaoteng Ma; Le Wan; Runze Liu 002; Xiu Li 001; Zongqing Lu 002 (ICLR, 2024)

FreqMark: Invisible Image Watermarking via Frequency Based Optimization in Latent Space. - Yiyang Guo; Ruizhe Li; Mude Hui; Hanzhong Guo; Chen Zhang; Chuangjian Cai; Le Wan; Shangfei Wang (NeurIPS, 2024)

Off-policy RL algorithms can be sample-efficient for continuous control via sample multiple reuse. - Jiafei Lyu; Le Wan; Xiu Li 001; Zongqing Lu 002 (Inf. Sci., 2024)

Understanding What Affects the Generalization Gap in Visual Reinforcement Learning: Theory and Empirical Evidence. - Jiafei Lyu; Le Wan; Xiu Li 001; Zongqing Lu 002 (J. Artif. Intell. Res., 2024)