| Inference for multiple heterogeneous networks with a common invariant subspace J Arroyo, A Athreya, J Cape, G Chen, CE Priebe, JT Vogelstein Journal of Machine Learning Research 22 (142), 1-49, 2021 | 116 | 2021 |
| Network classification with applications to brain connectomics JD Arroyo Relión, D Kessler, E Levina, SF Taylor The Annals of Applied Statistics 13 (3), 1648-1677, 2019 | 89 | 2019 |
| Joint embedding of graphs S Wang, J Arroyo, JT Vogelstein, CE Priebe IEEE transactions on pattern analysis and machine intelligence 43 (4), 1324-1336, 2019 | 75 | 2019 |
| Statistical connectomics J Chung, E Bridgeford, J Arroyo, BD Pedigo, A Saad-Eldin, ... Annual Review of Statistics and Its Application 8 (1), 463-492, 2021 | 32 | 2021 |
| Joint embedding: A scalable alignment to compare individuals in a connectivity space KH Nenning, T Xu, E Schwartz, J Arroyo, A Woehrer, AR Franco, ... NeuroImage 222, 117232, 2020 | 32 | 2020 |
| The importance of being correlated: Implications of dependence in joint spectral inference across multiple networks K Pantazis, A Athreya, J Arroyo, WN Frost, ES Hill, V Lyzinski Journal of Machine Learning Research 23 (141), 1-77, 2022 | 13 | 2022 |
| Multiple network embedding for anomaly detection in time series of graphs G Chen, J Arroyo, A Athreya, J Cape, JT Vogelstein, Y Park, C White, ... arXiv preprint arXiv:2008.10055, 2020 | 13 | 2020 |
| Efficient distributed estimation of inverse covariance matrices J Arroyo, E Hou 2016 IEEE Statistical Signal Processing Workshop (SSP), 1-5, 2016 | 10 | 2016 |
| Joint spectral clustering in multilayer degree-corrected stochastic blockmodels J Agterberg, Z Lubberts, J Arroyo arXiv preprint arXiv:2212.05053, 2022 | 7 | 2022 |
| Valid two‐sample graph testing via optimal transport Procrustes and multiscale graph correlation with applications in connectomics J Chung, B Varjavand, J Arroyo‐Relión, A Alyakin, J Agterberg, M Tang, ... Stat 11 (1), e429, 2022 | 7* | 2022 |
| Overlapping community detection in networks via sparse spectral decomposition J Arroyo, E Levina Sankhya A 84 (1), 1-35, 2022 | 7 | 2022 |
| Manifold oblique random forests: Towards closing the gap on convolutional deep networks A Li, R Perry, C Huynh, TM Tomita, R Mehta, J Arroyo, J Patsolic, B Falk, ... SIAM Journal on Mathematics of Data Science 5 (1), 77-96, 2023 | 6* | 2023 |
| Effect of Mexico’s vaccination program on Covid-19 cases, hospitalizations, and deaths among older adults in Mexico City NC Gasca, J Reyes-Garza, S Lozano-Esparza, P Orozco-del Pino, ... salud pública de méxico 64 (4, jul-ago), 424-428, 2022 | 6 | 2022 |
| Maximum likelihood estimation and graph matching in errorfully observed networks J Arroyo, DL Sussman, CE Priebe, V Lyzinski Journal of Computational and Graphical Statistics 30 (4), 1111-1123, 2021 | 6 | 2021 |
| Simultaneous prediction and community detection for networks with application to neuroimaging J Arroyo, E Levina arXiv preprint arXiv:2002.01645, 2020 | 5 | 2020 |
| Joint embedding: A scalable alignment to compare individuals in a connectivity space. NeuroImage, 222, Article 117232 KH Nenning, T Xu, E Schwartz, J Arroyo, A Woehrer, AR Franco, ... | 5 | 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 | 5* | 2019 |
| Graph independence testing J Xiong, C Shen, J Arroyo, JT Vogelstein arXiv preprint arXiv:1906.03661, 2019 | 4 | 2019 |
| Graph matching between bipartite and unipartite networks: to collapse, or not to collapse, that is the question J Arroyo, CE Priebe, V Lyzinski IEEE transactions on network science and engineering 8 (4), 3019-3033, 2021 | 2 | 2021 |
| Learning Joint and Individual Structure in Network Data with Covariates C James, D Yuan, I Gaynanova, J Arroyo arXiv preprint arXiv:2406.08776, 2024 | | 2024 |
Joshua T. VogelsteinDept of Biomedical Engineering, Johns Hopkins UniversityVerified email at jhu.edu
