Pre-prints

1. K. Konishcheva, B. Leventhal, M. Koyama, S. Panda, J. T. Vogelstein, M. Milham, A. Lindner, and A. Klein. Accurate and efficient data-driven psychiatric assessment using machine learning. PsyArXiv, 2024.
2. J. Chung, E. W. Bridgeford, M. Powell, D. Pisner, T. Xu, and J. T. Vogelstein. Are human connectomes heritable? bioRxiv, 2024.
3. S. Panda, C. Shen, R. Perry, J. Zorn, A. Lutz, C. E. Priebe, and J. T. Vogelstein. High-Dimensional and Universally Consistent K-Sample Tests. arXiv, 2023.
4. C. Shen, S. Panda, and J. T. Vogelstein. Learning Interpretable Characteristic Kernels via Decision Forests. arXiv, 2023.
5. Eric W. Bridgeford, Jaewon Chung, Brian Gilbert, Sambit Panda, Adam Li, Cencheng Shen, Alexandra Badea, Brian Caffo, and Joshua T. Vogelstein. Learning sources of variability from high-dimensional observational studies. arXiv, 2023.
6. J. Dey, W. LeVine, H. Xu, A. De Silva, T. M. Tomita, A. Geisa, T. Chu, J. Desman, and J. T. Vogelstein. Deep Discriminative to Kernel Generative Networks for In- and Out-of-distribution Calibrated Inference. arXiv, 2022.
7. T. Xu, J. Cho, G. Kiar, E. W. Bridgeford, J. T. Vogelstein, and M. P. Milham. A Guide for Quantifying and Optimizing Measurement Reliability for the Study of Individual Differences. bioRxiv, 2022.
8. Haoyin Xu, Jayanta Dey, Sambit Panda, and Joshua T. Vogelstein. Simplest Streaming Trees. arXiv, 2021.
9. Haoyin Xu, Kaleab A. Kinfu, Will LeVine, Sambit Panda, Jayanta Dey, Michael Ainsworth and Yu-Chung Peng, Madi Kusmanov, Florian Engert, Christopher M. White, Joshua T. Vogelstein, and Carey E. Priebe. When are Deep Networks really better than Decision Forests at small sample sizes, and how? arXiv, 2021.
10. S. Panda, S. Palaniappan, J. Xiong, E. W. Bridgeford, . Mehta, C. Shen, and J. T. Vogelstein. hyppo: A Multivariate Hypothesis Testing Python Package. arXiv, 2021.
11. V. Gopalakrishnan, J. Chung, E. Bridgeford, B. D. Pedigo, J. Arroyo, L. Upchurch, G. A. Johnsom, N. Wang, Y. Park, C. E. Priebe, and J. T. Vogelstein. Discovery of Multi-Level Network Differences Across Populations of Heterogeneous Connectomes. arXiv, 2020.
12. J. T. Vogelstein, J. Dey, H. S. Helm, W. LeVine, Mehta, Ronak D, T. M. Tomita, H. Xu, A. Geisa, Q. Wang, . M. van de Ven, and others. A Simple Lifelong Learning Approach. arXiv, 2020.