Pre-Prints


Pre-prints
  1. 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. Multiscale Comparative Connectomics. arXiv, 2020.
  2. L. Rose, L. Graham, A. Koenecke, M. Powell, R. Xiong, Z. Shen, K. W. Kinzler, C. Bettegowda, B. Vogelstein, M. F. Konig, S. Athey, J. T. Vogelstein, and T. H. Wagner. The Association Between Alpha-1 Adrenergic Receptor Antagonists and In-Hospital Mortality from COVID-19. medRxiv, 2020.
  3. H. S. Helm, R. D. Mehta, B. Duderstadt, W. Yang, C. M. White, A. Geisa, J. T. Vogelstein, and C. E. Priebe. A partition-based similarity for classification distributions. arXiv, 2020.
  4. J. T. Vogelstein, E. Bridgeford, M. Tang, D. Zheng, R. Burns, and M. Maggioni. Geometric Dimensionality Reduction for Big Data. arXiv, 2020.
  5. E. W. Bridgeford, S. Wang, Z. Yang, Z. Wang, T. Xu, C. Craddock, J. Dey, G. Kiar, W. Gray-Roncal, C. Coulantoni, C. Douville, C. E. Priebe, B. Caffo, M. Milham, X. Zuo, and J. T. Vogelstein. Eliminating accidental deviations to minimize generalization error with applications in connectomics and genomics. bioRxiv, 2020.
  6. Guodong Chen, Jesús Arroyo, Avanti Athreya, Joshua Cape, Joshua T. Vogelstein, Youngser Park, Chris White, Jonathan Larson, Weiwei Yang, and Carey E. Priebe. Multiple Network Embedding for Anomaly Detection in Time Series of Graphs. arXiv, 2020.
  7. K. Mehta, R. F. Goldin, D. Marchette, J. T. Vogelstein, C. E. Priebe, and G. A. Ascoli. Neuronal Classification from Network Connectivity via Adjacency Spectral Embedding. bioRxiv, 2020.
  8. C. E. Priebe, J. T. Vogelstein, F. Engert, and C. M. White. Modern Machine Learning: Partition & Vote. bioRxiv, 2020.
  9. A. Koenecke, M. Powell, R. Xiong, Z. Shen, N. Fischer, S. Huq, A. M. Khalafallah, M. Trevisan, P. Sparen, J. J. Carrero, A. Nishimura, B. Caffo, E. A. Stuart, R. Bai, V. Staedtke, N. Papadopoulos, K. W. Kinzler, B. Vogelstein, S. Zhou, C. Bettegowda, M. F. Konig, B. Mensh, J. T. Vogelstein, and S. Athey. Alpha-1 adrenergic receptor antagonists to prevent hyperinflammation and death from lower respiratory tract infection. arXiv, 2020.
  10. M. Konig, M. Powell, V. Staedtke, R. Bai, D. L. Thomas, N. Fischer, S. Huq, A. M. Khalafallah, A. Koenecke, R. Xiong, B. Mensh, N. Papadopoulos, K. W. Kinzler, B. Vogelstein, J. T. Vogelstein, S. Athey, S. Zhou, and C. Bettegowda. Targeting the catecholamine-cytokine axis to prevent SARS-CoV-2 cytokine storm syndrome. medRxiv, 2020.
  11. A. Nikolaidis, A. S. Heinsfeld, T. Xu, P. Bellec, J. T. Vogelstein, and M. Milham. Bagging Improves Reproducibility of Functional Parcellation of the Human Brain. NeuroImage, 2020.
  12. E. W. Bridgeford, S. Wang, Z. Yang, Z. Wang, T. Xu, C. Craddock, J. Dey, G. Kiar, W. Gray-Roncal, C. Coulantoni, C. Douville, C. E. Priebe, B. Caffo, M. Milham, X. Zuo, (CoRR), and J. T. Vogelstein. Big Data Reproducibility: Applications in Brain Imaging and Genomics. bioRxiv, 2020.
  13. Joshua T. Vogelstein, Hayden S. Helm, Ronak D. Mehta, Jayanta Dey, Will LeVine, Weiwei Yang, Bryan Tower, Jonathan Larson, Chris White, and Carey E. Priebe. A general approach to progressive learning. None, 2020.
  14. Ronan Perry, Gavin Mischler, Richard Guo, Theodore Lee, Alexander Chang, Arman Koul, Cameron Franz, and Joshua T. Vogelstein. mvlearn: Multiview Machine Learning in Python. None, 2020.
  15. Tyler M. Tomita and Joshua T. Vogelstein. Robust Similarity and Distance Learning via Decision Forests. None, 2020.
  16. C. Shen and J. T. Vogelstein. The Chi-Square Test of Distance Correlation. None, 2019.
  17. E. W. Bridgeford, S. Wang, Z. Yang, Z. Wang, T. Xu, C. Craddock, G. Kiar, W. Gray-Roncal, C. E. Priebe, B. Caffo, M. Milham, X. Zuo, (CoRR), and J. T. Vogelstein. Optimal Experimental Design for Big Data: Applications in Brain Imaging. bioRxiv, 2019.
  18. R. Mehta, C. Shen, T. Xu, and J. T. Vogelstein. A Consistent Independence Test for Multivariate Time-Series. arxiv, 2019.
  19. R. Perry, T. M. Tomita, J. Patsolic, B. Falk, and J. T. Vogelstein. Manifold Forests: Closing the Gap on Neural Networks. arXiv, 2019.
  20. S. Panda, S. Palaniappan, J. Xiong, A. Swaminathan, S. Ramachandran, E. W. Bridgeford, C. Shen, and J. T. Vogelstein. mgcpy: A Comprehensive High Dimensional Independence Testing Python Package. arXiv, 2019.
  21. J. Arroyo, A. Athreya, J. Cape, G. Chen, C. E. Priebe, and J. T. Vogelstein. Inference for multiple heterogenous networks with a common invariant subspace. arXiv, 2019.
  22. H. Helm, J. V. Vogelstein, and C. E. Priebe. Vertex Classification on Weighted Networks. arXiv, 2019.
  23. R. Mehta, R. Guo, J. Arroyo, M. Powell, H. Helm, C. Shen, and J. T. Vogelstein. Estimating Information-Theoretic Quantities with Uncertainty Forests. arXiv e-prints, 2019.
  24. J. Xiong, C. Shen, J. Arroyo, and J. T. Vogelstein. Graph Independence Testing. arXiv, 2019.
  25. D. Mhembere, D. Zheng, C. E. Priebe, J. T. Vogelstein, and R. Burns. clusterNOR: A NUMA-Optimized Clustering Framework. arxiv, 2019.
  26. T. L. Athey and J. T. Vogelstein. AutoGMM: Automatic Gaussian Mixture Modeling in Python. arxiv, 2019.
  27. A. Branch, D. Tward, J. T. Vogelstein, Z. Wu, and M. Gallagher. An optimized protocol for iDISCO+ rat brain clearing, imaging, and analysis. bioRxiv, 2019.
  28. C. Shen and J. T. Vogelstein. Decision Forests Induce Characteristic Kernels. arXiv, 2018.
  29. D. S. Greenberg, D. J. Wallace, K. Voit, S. Wuertenberger, U. Czubayko, A. Monsees, T. Handa, J. T. Vogelstein, R. Seifert, Y. Groemping, and J. N. Kerr. Accurate action potential inference from a calcium sensor protein through biophysical modeling. bioRxiv, 2018.
  30. S. Wang, C. Shen, A. Badea, C. E. Priebe, and J. T. Vogelstein. Signal Subgraph Estimation Via Vertex Screening. arXiv, 2018.
  31. R. Tang, M. Tang, J. T. Vogelstein, and C. E. Priebe. Robust Estimation from Multiple Graphs under Gross Error Contamination. arXiv, 2017.
  32. H. Patsolic, S. Adali, J. T. Vogelstein, Y. Park, C. E. Priebe, G. Li, and V. Lyzinski. Seeded Graph Matching Via Joint Optimization of Fidelity and Commensurability. arXiv, 2014.