Reports


Technical Reports
  1. Ronan Perry, Ronak Mehta, Richard Guo, Eva Yezerets, Jesús Arroyo, Mike Powell and Hayden Helm, Cencheng Shen, and Joshua T. Vogelstein. Random Forests for Adaptive Nearest Neighbor Estimation of Information-Theoretic Quantities. arXiv, 2021.
  2. Ali Saad-Eldin, Benjamin D. Pedigo, Carey E. Priebe, and Joshua T. Vogelstein. Graph Matching via Optimal Transport. arXiv, 2021.
  3. Jayanta Dey, Ali Geisa, Ronak Mehta, Tyler M. Tomita, Hayden S. Helm, Eric Eaton, Jeffery Dick, Carey E. Priebe, and Joshua T. Vogelstein. Towards a theory of out-of-distribution learning. arXiv, 2021.
  4. 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.
  5. Jaewon Chung, Eric Bridgeford, Jesus Arroyo, Benjamin D. Pedigo, Ali Saad-Eldin, Vivek Gopalakrishnan, Liang Xiang, Carey E. Priebe, and Joshua Vogelstein. Statistical Connectomics. arXiv, 2020.
  6. J. T. Vogelstein. P-Values in a Post-Truth World. arXiv, 2020.
  7. H. S. Helm, A. Basu, A. Athreya, Y. Park, J. T. Vogelstein, M. Winding, M. Zlatic, A. Cardona, P. Bourke, J. Larson, C. White, and C. E. Priebe. Learning to rank via combining representations. arXiv, 2020.
  8. C. E. Priebe, J. T. Vogelstein, F. Engert, and C. M. White. Modern Machine Learning: Partition Vote. bioRxiv, 2020.
  9. Polina Golland, Jack Gallant, Greg Hager, Hanspeter Pfister, Christos Papadimitriou, Stefan Schaal, and Joshua T. Vogelstein. A New Age of Computing and the Brain. arXiv, 2020.
  10. Tyler M. Tomita and Joshua T. Vogelstein. Robust Similarity and Distance Learning via Decision Forests. arXiv, 2020.
  11. D. Mhembere, D. Zheng, J. T. Vogelstein, C. E. Priebe, and R. Burns. Graphyti: A Semi-External Memory Graph Library for FlashGraph. arXiv, 2019.
  12. H. Helm, J. V. Vogelstein, and C. E. Priebe. Vertex Classification on Weighted Networks. arXiv, 2019.
  13. D. Mhembere, D. Zheng, C. E. Priebe, J. T. Vogelstein, and R. Burns. clusterNOR: A NUMA-Optimized Clustering Framework. arxiv, 2019.
  14. 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.
  15. 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.
  16. G. Kiar, E. Bridgeford, W. G. Roncal, (CoRR), V. Chandrashekhar, D. Mhembere, S. Ryman, X. Zuo, D. S. Marguiles, R. C. Craddock, C. E. Priebe, R. Jung, V. Calhoun, B. Caffo, R. Burns, M. P. Milham, and J. Vogelstein. A High-Throughput Pipeline Identifies Robust Connectomes But Troublesome Variability. bioRxiv, 2018.
  17. G. Kiar, R. J. Anderson, A. Baden, A. Badea, E. W. Bridgeford, A. Champion, V. Chandrashekhar, F. Collman, B. Duderstadt, A. C. Evans, F. Engert, B. Falk, T. Glatard, W. R. G. Roncal, D. N. Kennedy, J. Maitin-Shepard, R. A. Marren, O. Nnaemeka, E. Perlman, S. Seshamani, E. T. Trautman, D. J. Tward, P. A. Valdés-Sosa, Q. Wang, M. I. Miller, R. Burns, and J. T. Vogelstein. NeuroStorm: Accelerating Brain Science Discovery in the Cloud. arXiv, 2018.
  18. S. Wang, C. Shen, A. Badea, C. E. Priebe, and J. T. Vogelstein. Signal Subgraph Estimation Via Vertex Screening. arXiv, 2018.
  19. R. Tang, M. Tang, J. T. Vogelstein, and C. E. Priebe. Robust Estimation from Multiple Graphs under Gross Error Contamination. arXiv, 2017.
  20. C. E. Priebe, Y. Park, M. Tang, A. Athreya, V. Lyzinski, J. T. Vogelstein, Y. Qin, B. Cocanougher, K. Eichler, M. Zlatic, and A. Cardona. Semiparametric spectral modeling of the Drosophila connectome. arXiv, 2017.
  21. D. Zheng, D. Mhembere, J. T. Vogelstein, C. E. Priebe, and R. Burns. FlashR: R-Programmed Parallel and Scalable Machine Learning using SSDs. CoRR, abs/1604.06414, 2017.
  22. D. Zheng, R. Burns, J. Vogelstein, C. E. Priebe, and A. S. Szalay. An SSD-based eigensolver for spectral analysis on billion-node graphs. arXiv, 2016.
  23. A. Sinha, W. Roncal, and N. Kasthuri. Automatic Annotation of Axoplasmic Reticula in Pursuit of Connectomes. arXiv, 2014.
  24. M. Kazhdan, R. Burns, B. Kasthuri, J. Lichtman, J. Vogelstein, and J. Vogelstein. Gradient-Domain Processing for Large EM Image Stacks. arXiv, 2013.
  25. A. Banerjee, J. Vogelstein, and D. Dunson. Parallel inversion of huge covariance matrices. arXiv, 2013.