| Likelihood Ratio Tests for a Large Directed Acyclic Graph C Li, X Shen, W Pan Journal of the American Statistical Association 115 (531), 1304-1319, 2020 | 21 | 2020 |
| Nonlinear Causal Discovery with Confounders C Li, X Shen, W Pan Journal of the American Statistical Association, 1-21, 2023 | 14 | 2023 |
| Inference for a Large Directed Acyclic Graph with Unspecified Interventions C Li, X Shen, W Pan Journal of Machine Learning Research 24 (73), 1-48, 2023 | 10* | 2023 |
| Discovery and Inference of a Causal Network with Hidden Confounding L Chen, C Li, X Shen, W Pan Journal of the American Statistical Association, 1-27, 2023 | 3 | 2023 |
| Inference of nonlinear causal effects with application to TWAS with GWAS summary data B Dai, C Li, H Xue, W Pan, X Shen Causal Learning and Reasoning, 793-826, 2024 | 2* | 2024 |
| Inferring a directed acyclic graph of phenotypes from GWAS summary statistics R Zilinskas, C Li, X Shen, W Pan, T Yang Biometrics 80 (1), ujad039, 2024 | 2 | 2024 |
| RankSEG: A Consistent Ranking-based Framework for Segmentation B Dai, C Li Journal of Machine Learning Research 24 (224), 1-50, 2023 | 1 | 2023 |
| Speeding up Interval Estimation for R2-based Mediation Effect of High-dimensional Mediators via Cross-fitting Z Xu, C Li, S Chi, T Yang, P Wei bioRxiv, 2023.02. 06.527391, 2023 | 1 | 2023 |
| Data-adaptive Discriminative Feature Localization with Statistically Guaranteed Interpretation B Dai, X Shen, LY Chen, C Li, W Pan The Annals of Applied Statistics 17 (3), 2019-2038, 2023 | | 2023 |
Wei PanUniversity of Minnesota在 umn.edu 的电子邮件经过验证
