| The chi-square test of distance correlation C Shen, S Panda, JT Vogelstein Journal of Computational and Graphical Statistics 31 (1), 254-262, 2022 | 77 | 2022 |
| From distance correlation to multiscale graph correlation C Shen, CE Priebe, JT Vogelstein Journal of the American Statistical Association 115 (529), 280-291, 2020 | 76 | 2020 |
| Sparse projection oblique randomer forests TM Tomita, J Browne, C Shen, J Chung, JL Patsolic, B Falk, CE Priebe, ... Journal of machine learning research 21 (104), 1-39, 2020 | 66 | 2020 |
| The exact equivalence of distance and kernel methods in hypothesis testing C Shen, JT Vogelstein AStA Advances in Statistical Analysis 105, 385-403, 2021 | 50 | 2021 |
| Generalized canonical correlation analysis for classification C Shen, M Sun, M Tang, CE Priebe Journal of Multivariate Analysis 130, 310-322, 2014 | 47 | 2014 |
| Discovering and deciphering relationships across disparate data modalities JT Vogelstein, EW Bridgeford, Q Wang, CE Priebe, M Maggioni, C Shen eLife 8, e41690, 2019 | 41* | 2019 |
| One-Hot Graph Encoder Embedding C Shen, Q Wang, CE Priebe IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (6), 7933 …, 2023 | 31 | 2023 |
| Network dependence testing via diffusion maps and distance-based correlations Y Lee, C Shen, CE Priebe, JT Vogelstein Biometrika 106 (4), 857-873, 2019 | 30 | 2019 |
| hyppo: A multivariate hypothesis testing Python package S Panda, S Palaniappan, J Xiong, EW Bridgeford, R Mehta, C Shen, ... arXiv preprint arXiv:1907.02088, 2019 | 21* | 2019 |
| Universally consistent K-sample tests via dependence measures S Panda, C Shen, R Perry, J Zorn, A Lutz, CE Priebe, JT Vogelstein Statistics & Probability Letters 216, 110278, 2025 | 20* | 2025 |
| Manifold matching using shortest-path distance and joint neighborhood selection C Shen, JT Vogelstein, CE Priebe Pattern Recognition Letters 92, 41-48, 2017 | 20 | 2017 |
| Robust vertex classification L Chen, C Shen, JT Vogelstein, CE Priebe IEEE Transactions on Pattern Analysis and Machine Intelligence 38 (3), 578-590, 2016 | 20 | 2016 |
| Discovering the signal subgraph: An iterative screening approach on graphs C Shen, S Wang, A Badea, CE Priebe, JT Vogelstein Pattern Recognition Letters 184, 97-102, 2024 | 17* | 2024 |
| Sparse representation classification beyond ℓ1 minimization and the subspace assumption C Shen, L Chen, Y Dong, CE Priebe IEEE Transactions on Information Theory 66 (8), 5061-5071, 2020 | 16 | 2020 |
| Estimating information-theoretic quantities with uncertainty forests R Guo, R Mehta, J Arroyo, H Helm, C Shen, JT Vogelstein arXiv, arXiv: 1907.00325, 2019 | 11* | 2019 |
| Independence testing for temporal data C Shen, J Chung, R Mehta, T Xu, JT Vogelstein Transactions on Machine Learning Research, 2024 | 10* | 2024 |
| Discovering Communication Pattern Shifts in Large-Scale Labeled Networks Using Encoder Embedding and Vertex Dynamics C Shen, J Larson, H Trinh, X Qin, Y Park, CE Priebe IEEE Transactions on Network Science and Engineering 11 (2), 2100 - 2109, 2024 | 9* | 2024 |
| Synergistic graph fusion via encoder embedding C Shen, C Priebe, J Larson, H Trinh Information Sciences 678, 120912, 2024 | 8 | 2024 |
| Graph Encoder Ensemble for Simultaneous Vertex Embedding and Community Detection C Shen, Y Park, CE Priebe 2023 International Conference on Algorithms, Data Mining, and Information …, 2023 | 8 | 2023 |
| Community correlations and testing independence between binary graphs C Shen, J Arroyo, J Xiong, JT Vogelstein arXiv preprint arXiv:1906.03661, 2019 | 8* | 2019 |
Joshua T. VogelsteinDept of Biomedical Engineering, Johns Hopkins UniversityVerified email at jhu.edu
