| Optimal change point detection and localization in sparse dynamic networks D Wang, Y Yu, A Rinaldo | 109 | 2021 |
| Univariate mean change point detection: Penalization, cusum and optimality D Wang, Y Yu, A Rinaldo | 108 | 2020 |
| Optimal covariance change point localization in high dimensions D Wang, Y Yu, A Rinaldo | 89* | 2021 |
| Statistical analysis of persistence intensity functions YC Chen, D Wang, A Rinaldo, L Wasserman arXiv preprint arXiv:1510.02502, 2015 | 54 | 2015 |
| Statistically and computationally efficient change point localization in regression settings D Wang, Z Zhao, KZ Lin, R Willett Journal of Machine Learning Research 22 (248), 1-46, 2021 | 50 | 2021 |
| Optimal nonparametric multivariate change point detection and localization OHM Padilla, Y Yu, D Wang, A Rinaldo IEEE Transactions on Information Theory 68 (3), 1922-1944, 2021 | 47 | 2021 |
| Localizing changes in high-dimensional regression models A Rinaldo, D Wang, Q Wen, R Willett, Y Yu International Conference on Artificial Intelligence and Statistics, 2089-2097, 2021 | 45 | 2021 |
| Optimal nonparametric change point analysis OH Madrid Padilla, Y Yu, D Wang, A Rinaldo | 43* | 2021 |
| Dbscan: Optimal rates for density-based cluster estimation D Wang, X Lu, A Rinaldo Journal of machine learning research 20 (170), 1-50, 2019 | 41* | 2019 |
| Localizing changes in high-dimensional vector autoregressive processes D Wang, Y Yu, A Rinaldo, R Willett arXiv preprint arXiv:1909.06359, 2019 | 35 | 2019 |
| A note on online change point detection Y Yu, OH Madrid Padilla, D Wang, A Rinaldo Sequential Analysis 42 (4), 438-471, 2023 | 24 | 2023 |
| Change-point inference in high-dimensional regression models under temporal dependence H Xu, D Wang, Z Zhao, Y Yu The Annals of Statistics 52 (3), 999-1026, 2024 | 23 | 2024 |
| Optimal network online change point localisation Y Yu, OHM Padilla, D Wang, A Rinaldo arXiv preprint arXiv:2101.05477, 2021 | 19 | 2021 |
| Change-point detection for sparse and dense functional data in general dimensions CM Madrid Padilla, D Wang, Z Zhao, Y Yu Advances in Neural Information Processing Systems 35, 37121-37133, 2022 | 13 | 2022 |
| Optimal change-point testing for high-dimensional linear models with temporal dependence Z Zhao, X Luo, Z Liu, D Wang arXiv preprint arXiv:2205.03880, 2022 | 12 | 2022 |
| Functional linear regression with mixed predictors D Wang, Z Zhao, Y Yu, R Willett Journal of Machine Learning Research 23 (266), 1-94, 2022 | 12 | 2022 |
| Nonparametric clustering of functional data using pseudo-densities M Ciollaro, CR Genovese, D Wang | 11 | 2016 |
| changepoints: A Collection of Change-Point Detection Methods H Xu, O Padilla, D Wang, M Li R package version 1 (0), 2022 | 10 | 2022 |
| Detecting abrupt changes in high-dimensional self-exciting Poisson processes D Wang, Y Yu, R Willett arXiv preprint arXiv:2006.03572, 2020 | 8 | 2020 |
| Divide and conquer dynamic programming: An almost linear time change point detection methodology in high dimensions W Li, D Wang, A Rinaldo International Conference on Machine Learning, 20065-20148, 2023 | 6 | 2023 |
