NEWS
- Our paper: "Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness "Bohang Zhang, Jingchu Gai, Yiheng Du, Qiwei Ye, Di He, Liwei Wang , has been accepted by ICLR 2024 (Oral) !
- Our paper: "A Computational Framework for Neural Network-based Variational Monte Carlo with Forward Laplacian "Ruichen Li, Haotian Ye, Du Jiang, Xuelan Wen, Chuwei Wang, Zhe Li, Xiang Li, Di He, Ji Chen, Weiluo Ren, Liwei Wang , has been accepted by Nature Machine Intelligence !
- Our paper: "Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective "Guhao Feng, Bohang Zhang, Yuntian Gu, Haotian Ye, Di He, Liwei Wang has been accepted by NeurIPS 2023 (Oral) !
- Our paper: "A Reduction-based Framework for Sequential Decision Making with Delayed Feedback "Yunchang Yang, Han Zhong, Tianhao Wu, Bin Liu, Liwei Wang , Simon S. Du has been accepted by NeurIPS 2023 !
- Our paper: "Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds "Jiayi Huang, Han Zhong,Liwei Wang , Lin F. Yang has been accepted by NeurIPS 2023 !
- Our paper: "PRED: Pre-training via Semantic Rendering on LiDAR Point Clouds "Hao Yang, Haiyang Wang, Di Dai, Liwei Wang , has been accepted by NeurIPS 2023 !
- Our paper: "Offline Meta Reinforcement Learning with In-Distribution Online Adaptation "Jianhao Wang, Jin Zhang, Haozhe Jiang, Junyu Zhang, Liwei Wang , Chongjie Zhang has been accepted by ICML 2023 !
- Our paper: "A Complete Expressiveness Hierarchy for Subgraph GNNs via Subgraph Weisfeiler-Lehman Tests " Bohang Zhang, Guhao Feng, Yiheng Du, Di He, Liwei Wang , has been accepted by ICML 2023 !
- Our paper: "On the Power of Pre-training for Generalization in RL: Provable Benefits and Hardness " Haotian Ye, Xiaoyu Chen, Liwei Wang , Simon Du, has been accepted by ICML 2023 !
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Our paper: ¡°Rethinking the Expressive Power of GNNs via Graph Biconnectivity ¡±,
Bohang Zhang, Shengjie Luo, Liwei Wang , Di He,
received the ICLR 2023 Outstanding Paper Award!
- Our paper: "Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game " Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Liwei Wang , Tong Zhang, has been accepted by ICLR 2023 !
RECENT PUBLICATIONS (Full Paper List)
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Quanlin Wu, Hang Ye, Yuntian Gu, Huishuai Zhang,Liwei Wang , Di He, ¡°Denoising Masked AutoEncoders Helps Robust Classification ¡±, International Conference on Learning Representations (ICLR), 2023
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Jiachen Hu, Han Zhong, Chi Jin, Liwei Wang , ¡°Provable Sim-to-real Transfer in Continuous Domain with Partial Observations ¡±, International Conference on Learning Representations (ICLR), 2023
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Shengjie Luo, Tianlang Chen, Yixian Xu, Shuxin Zheng, Tie-Yan Liu, Liwei Wang , Di He, ¡°One Transformer Can Understand Both 2D & 3D Molecular Data ¡±, International Conference on Learning Representations (ICLR), 2023
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Keyu Tian, Yi Jiang, Qishuai Diao, Chen Lin, Liwei Wang , Zehuan Yuan, ¡°Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling ¡±, International Conference on Learning Representations (ICLR), 2023 (Spotlight)
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Haiyang Wang, Lihe Ding, Shaocong Dong, Shaoshuai Shi, Aoxue Li, Jianan Li, Zhenguo Li, Liwei Wang , ¡°CAGroup3D: Class-Aware Grouping for 3D Object Detection on Point Clouds ¡±, Conference on Neural Information Processing Systems (NeurIPS), 2022
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Bohang Zhang, Du Jiang, Di He, Liwei Wang , ¡°Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean Function Perspective ¡±, Conference on Neural Information Processing Systems (NeurIPS), 2022 (Oral)
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Shengjie Luo, Shanda Li, Shuxin Zheng, Tie-Yan Liu, Liwei Wang , Di He, ¡°Your Transformer May Not be as Powerful as You Expect ¡±, Conference on Neural Information Processing Systems (NeurIPS), 2022
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Binghui Li, Jikai Jin, Han Zhong, John E. Hopcroft,Liwei Wang , ¡°Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power ¡±, Conference on Neural Information Processing Systems (NeurIPS), 2022
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Chuwei Wang, Shanda Li, Di He, Liwei Wang , ¡°Is L2 Physics-Informed Loss Always Suitable for Training Physics-Informed Neural Network ¡±, Conference on Neural Information Processing Systems (NeurIPS), 2022
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Dong Wang, Zhao Zhang, Ziwei Zhao, Yuhang Liu, Yihong Chen, Liwei Wang , ¡°PointScatter: Point Set Representation for Tubular Structure Extraction ¡±, European Conference on Computer Vision (ECCV), 2022
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Ziwei Zhao, Dong Wang, Yihong Chen, Ziteng Wang, Liwei Wang , ¡°Check and Link: Pairwise Lesion Correspondence Guides Mammogram Mass Detection ¡±, European Conference on Computer Vision (ECCV), 2022
Full publication list here
Students
Current Students
| PhD Students | Master Students | Undergraduate Students |
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Postdoctoral
- Dong Wang
- Tianle Cai (Princeton)
- Shengcao Cao (CMU)
- Siyu Chen (CMU)
- Yifan Chen (Caltech)
- Yihong Chen (ETH Zurich)
- Yuxi Chen (Google)
- Yuting Dai (YIZHUN)
- Chen Dan (CMU)
- Xiaocheng Deng (Microsoft)
- Jia Ding (YIZHUN)
- Kefan Dong (Stanford)
- Xialiang Dou (University of Chicago)
- Kai Fan (Alibaba)
- Jun Gao (University of Toronto)
- Ruiqi Gao (Princeton)
- Linyuan Gong (UC Berkeley)
- Jiayuan Gu (UCSD)
- Di He (Peking University)
- Lunjia Hu (Stanford)
- Zhiqiang Hu (SenseTime)
- Hanzhe Hu (ETH Zurich)
- Baihe Huang (UC Berkeley)
- He Jiang (University of Southern California)
- Chi Jin (Princeton)
- Zhaoxiang Jing (China Everbright Bank)
- Aoxue Li (Huawei)
- Haochuan Li (MIT)
- Ke Lin (Samsung)
- Tianhong Li (MIT)
- Shanda Li (CMU)
- Yao Liu (Stanford)
- Yuhan Liu (Cornell University)
- Zhuohan Li (UC Berkeley)
- Tiange Luo (UMich)
- Yiping Lu (Stanford)
- Zhou Lu (Princeton)
- Wenlong Mou (UC Berkeley)
- Hongming Pu (University of Pennsylvania)
- Zihan Tan (University of Chicago)
- Feicheng Wang (Harvard University)
- Yichuan Wang (Microsoft)
- Yuanhao Wang (Princeton)
- Zhi Wang(Columbia University)
- Ziteng Wang (YIZHUN)
- Chenwei Wu (Duke University)
- Tianhao Wu (UC Berkeley)
- Yue Wu (UCLA)
- Jing Xu (Tsinghua University)
- Jinchen Xuan (UCSD)
- Ze Yang (U of T)
- Songbai Yan (UCSD)
- Hongyuan You (UCSB)
- Xuchen You (University of Maryland)
- Runtian Zhai (CMU)
- Xiyu Zhai (MIT)
- Chicheng Zhang (The University of Arizona)
- Hongyi Zhang (ByteDance)
- Jiaqi Zhang (YIZHUN)
- Kexin Zhang (YIZHUN)
- Mengxiao Zhang (University of Southern California)
- Yichen Zhang (NYU)
- Kai Zheng (Kuaishou)
- Yiqiao Zhong (Princeton)
- Yuchen Zhou (University of Wisconsin)
- Xu Zou (Tsinghua University)
Courses
Current Courses
- Machine Learning
- Information Theory
Previous Courses
- Statistical Learning