NEWS
- Our paper: "A Foundational Generative Model for Breast Ultrasound Image Analysis " by Haojun Yu, Youcheng Li, Nan Zhang, Zihan Niu, Xuantong Gong, Yanwen Luo, Haotian Ye, Siyu He, Quanlin Wu, Wangyan Qin, Mengyuan Zhou, Jie Han, Jia Tao, Ziwei Zhao, Di Dai, Di He, Dong Wang, Binghui Tang, Ling Huo, James Zou, Qingli Zhu, Yong Wang, Liwei Wang, has been accepted by Nature Biomedical Engineering !
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Our paper: "Visual autoregressive modeling: Scalable image generation via next-scale prediction
" by Keyu Tian, Yi Jiang, Zehuan Yuan, Bingyue Peng, Liwei Wang,
received the NeurIPS 2024 Best Paper Award!
! - Our paper: "Symmetry enforced solution of the many-body Schrödinger equation with deep neural network " by Zhe Li, Zixiang Lu, Ruichen Li, Xuelan Wen, Xiang Li, Liwei Wang, Ji Chen, Weiluo Ren, has been accepted by Nature Computational Science !
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Our paper: "Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness
" by Bohang Zhang, Jingchu Gai, Yiheng Du, Qiwei Ye, Di He, Liwei Wang,
received the ICLR 2024 Outstanding Paper Award Honorable Mention!
!
- Our paper: "A Computational Framework for Neural Network-based Variational Monte Carlo with Forward Laplacian " by 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 !
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Our paper: " Rethinking the Expressive Power of GNNs via Graph Biconnectivity
" by Bohang Zhang, Shengjie Luo, Liwei Wang, Di He,
received the ICLR 2023 Outstanding Paper Award!
RECENT PUBLICATIONS (Full Paper List)
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Haiyang Wang, Hao Tang, Li Jiang, Shaoshuai Shi, Muhammad Ferjad Naeem, Hongsheng Li, Bernt Schiele, Liwei Wang, "GiT: Towards Generalist Vision Transformer through Universal Language Interface", European Conference on Computer Vision (ECCV), 2024 (Oral)
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Han Zhong, Jiachen Hu, Yecheng Xue, Tongyang Li, Liwei Wang , "Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret", International Conference on Machine Learning (ICML), 2024
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Zhenyu He, Guhao Feng, Shengjie Luo, Kai Yang, Liwei Wang , Jingjing Xu, Zhi Zhang, Hongxia Yang, Di He, "Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation", International Conference on Machine Learning (ICML), 2024
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Kai Yang, Jan Ackermann, Zhenyu He, Guhao Feng, Bohang Zhang, Yunzhen Feng, Qiwei Ye, Di He, Liwei Wang , "Do Efficient Transformers Really Save Computation?", International Conference on Machine Learning (ICML), 2024
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Yexin Zhang, Chenyi Zhang, Cong Fang, Liwei Wang , Tongyang Li, "Quantum Algorithms and Lower Bounds for Finite-Sum Optimization", International Conference on Machine Learning (ICML), 2024
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Tianlang Chen, Shengjie Luo, Di He, Shuxin Zheng, Tie-Yan Liu, Liwei Wang , "GeoMFormer: A General Architecture for Geometric Molecular Representation Learning", International Conference on Machine Learning (ICML), 2024
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Guhao Feng, Bohang Zhang, Yuntian Gu, Haotian Ye, Di He, Liwei Wang , "Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective ", Conference on Neural Information Processing Systems (NeurIPS), 2023 (Oral)
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Yunchang Yang, Han Zhong, Tianhao Wu, Bin Liu, Liwei Wang , Simon S. Du, "A Reduction-based Framework for Sequential Decision Making with Delayed Feedback ", Conference on Neural Information Processing Systems (NeurIPS), 2023
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Jiayi Huang, Han Zhong,Liwei Wang , Lin F. Yang, "Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds ", Conference on Neural Information Processing Systems (NeurIPS), 2023
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Hao Yang, Haiyang Wang, Di Dai, Liwei Wang , "PRED: Pre-training via Semantic Rendering on LiDAR Point Clouds ", Conference on Neural Information Processing Systems (NeurIPS), 2023
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