| Debiased causal tree: Heterogeneous treatment effects estimation with unmeasured confounding C Tang, H Wang, X Li, Q Cui, YL Zhang, F Zhu, L Li, J Zhou, L Jiang Advances in Neural Information Processing Systems 35, 5628-5640, 2022 | 10 | 2022 |
| Harmless overparametrization in two-layer neural networks H Wang, W Lin arXiv e-prints, arXiv: 2106.04795, 2021 | 5 | 2021 |
| Heterogeneous federated learning on a graph H Wang, X Zhao, W Lin arXiv preprint arXiv:2209.08737, 2022 | 4 | 2022 |
| The Aggregation–Heterogeneity Trade-off in Federated Learning X Zhao, H Wang, W Lin The Thirty Sixth Annual Conference on Learning Theory, 5478-5502, 2023 | 2 | 2023 |
| CARE: Large Precision Matrix Estimation for Compositional Data S Zhang, H Wang, W Lin Journal of the American Statistical Association, 1-24, 2024 | 1 | 2024 |
| Difference-in-differences meets tree-based methods: heterogeneous treatment effects estimation with unmeasured confounding C Tang, H Wang, X Li, Q Cui, L Li, J Zhou International Conference on Machine Learning, 33792-33803, 2023 | 1 | 2023 |
| A Statistical Framework of Watermarks for Large Language Models: Pivot, Detection Efficiency and Optimal Rules X Li, F Ruan, H Wang, Q Long, WJ Su arXiv preprint arXiv:2404.01245, 2024 | | 2024 |
| Temporal Point Process Graphical Models Y Lyu, H Wang, W Lin arXiv preprint arXiv:2110.11562, 2021 | | 2021 |
Wei LinAssociate Professor of Statistics, Peking UniversityVerified email at math.pku.edu.cn
