Liwei Wang
教授
Researches machine learning theory, privacy-preserving algorithms and medical-imaging diagnosis systems.
Liwei Wang's lab at Peking works on learning theory & optimization and trustworthy & safe ML. 22 papers since 2023, 1 at top venues, mostly Nature Machine Intelligence. 10 PhD students and 10 master's students. 65 alumni, most often to Microsoft and Alibaba. Applications close .
At a glance
- papers, 2023–2026
- 6/ year
- at T1 venues
- 5%
- PhD students
- 10
- MS students
- 10
- alumni listed
- 65
Papers by yearfrom the lab homepage, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 1 papers2025 · T1 0
- 9 papers2024 · T1 1
- 12 papers2023 · T1 0
T1 venuesOtherVenues: Nature Machine Intelligence
Research focuspaper titles that use each topic's words
- Learning theory & optimization6 papers
- Trustworthy & safe ML0 papers
- privacy-preserving0 papers
- diagnosis0 papers
- intelligence science0 papers
Paper list
From the lab homepage.
20251 paper
- Nature Biomedical EngineeringA Foundational Generative Model for Breast Ultrasound Image Analysis (opens in a new tab)
20249 papers
- Nature Machine Intelligence (T1)A Computational Framework for Neural Network-based Variational Monte Carlo with Forward Laplacian (opens in a new tab)
- International Conference on Learning Representations (ICLR)Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness (opens in a new tab)
- International Conference on Machine Learning (ICML)Do Efficient Transformers Really Save Computation? (opens in a new tab)
- International Conference on Machine Learning (ICML)GeoMFormer: A General Architecture for Geometric Molecular Representation Learning (opens in a new tab)
- European Conference on Computer Vision (ECCV)GiT: Towards Generalist Vision Transformer through Universal Language Interface (opens in a new tab)
- International Conference on Machine Learning (ICML)Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret (opens in a new tab)
- International Conference on Machine Learning (ICML)Quantum Algorithms and Lower Bounds for Finite-Sum Optimization (opens in a new tab)
- International Conference on Machine Learning (ICML)Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation (opens in a new tab)
- Advances in Neural Information Processing Systems (NeurIPS)Visual autoregressive modeling: Scalable image generation via next-scale prediction (opens in a new tab)
202312 papers
- International Conference on Machine Learning (ICML)A Complete Expressiveness Hierarchy for Subgraph GNNs via Subgraph Weisfeiler-Lehman Tests (opens in a new tab)
- Conference on Neural Information Processing Systems (NeurIPS)A Reduction-based Framework for Sequential Decision Making with Delayed Feedback (opens in a new tab)
- International Conference on Learning Representations (ICLR)Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling (opens in a new tab)
- International Conference on Learning Representations (ICLR)Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game (opens in a new tab)
- International Conference on Machine Learning (ICML)Offline Meta Reinforcement Learning with In-Distribution Online Adaptation (opens in a new tab)
- International Conference on Machine Learning (ICML)On the Power of Pre-training for Generalization in RL: Provable Benefits and Hardness (opens in a new tab)
- International Conference on Learning Representations (ICLR)One Transformer Can Understand Both 2D & 3D Molecular Data (opens in a new tab)
- Conference on Neural Information Processing Systems (NeurIPS)PRED: Pre-training via Semantic Rendering on LiDAR Point Clouds (opens in a new tab)
- International Conference on Learning Representations (ICLR)Provable Sim-to-real Transfer in Continuous Domain with Partial Observations (opens in a new tab)
- International Conference on Learning Representations (ICLR)Rethinking the Expressive Power of GNNs via Graph Biconnectivity (opens in a new tab)
- Conference on Neural Information Processing Systems (NeurIPS)Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds (opens in a new tab)
- Conference on Neural Information Processing Systems (NeurIPS)Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective (opens in a new tab)
Where alumni went65 listed, 15% to industry
Industry 8Academia 47
Most often to
- Microsoft
- Alibaba
- ByteDance
Also to
- Princeton University
- Carnegie Mellon University
- UC Berkeley
Apply to PekingFall 2027
Computer Science PhD (international applicants)
- Round
- Main
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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