| Relaxing the assumptions of knockoffs by conditioning D Huang, L Janson The Annals of Statistics 48 (5), 3021-3042, 2020 | 52 | 2020 |
| On the optimality of sliced inverse regression in high dimensions Q Lin, X Li, D Huang, JS Liu | 28* | 2021 |
| Catalytic prior distributions with application to generalized linear models (vol 117, pg 12004, 2020) D Huang, N Stein, DB Rubin, SC Kou PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF …, 2020 | 16* | 2020 |
| Catalytic prior distributions with application to generalized linear models D Huang, N Stein, DB Rubin, SC Kou Proceedings of the National Academy of Sciences 117 (22), 12004-12010, 2020 | 16 | 2020 |
| Catalytic priors: Using synthetic data to specify prior distributions in bayesian analysis D Huang, F Wang, DB Rubin, SC Kou arXiv preprint arXiv:2208.14123, 2022 | 6 | 2022 |
| The Optimality of Kernel Classifiers in Sobolev Space J Lai, Z Li, D Huang, Q Lin arXiv preprint arXiv:2402.01148, 2024 | 3 | 2024 |
| Hypothesis Testing in Gaussian Graphical Models: Novel Goodness-of-Fit Tests and Conditional Randomization Tests X Lin, F Tian, D Huang arXiv preprint arXiv:2312.01815, 2023 | 1 | 2023 |
| Bayesian inference on Cox regression models using catalytic prior distributions W Li, D Huang arXiv preprint arXiv:2312.01411, 2023 | 1 | 2023 |
| On the Optimality of Functional Sliced Inverse Regression R Chen, S Tian, D Huang, Q Lin, JS Liu arXiv preprint arXiv:2307.02777, 2023 | 1 | 2023 |
| Sliced Inverse Regression with Large Structural Dimensions D Huang, S Tian, Q Lin arXiv preprint arXiv:2305.04340, 2023 | 1 | 2023 |
| Reliable and Flexible Inference for High Dimensional Data D Huang | 1 | 2020 |
| Using Synthetic Data to Regularize Maximum Likelihood Estimation W Li, D Huang arXiv preprint arXiv:2407.04194, 2024 | | 2024 |
| On the Structural Dimension of Sliced Inverse Regression D Huang, S Tian, Q Lin | | |
