Joshua Tzvi Vogelstein
Affiliations: | Johns Hopkins University, Baltimore, MD |
Area:
computational, circuit inference, fluorescence imagingGoogle:
"Joshua Vogelstein"Mean distance: 15.26 (cluster 17) | S | N | B | C | P |
Cross-listing: Computational Biology Tree
Parents
Sign in to add mentor| Daniel W. Moran | research assistant | Washington University | ||
| Eric D. Young | grad student | 2009 | Johns Hopkins | |
| (OOPSI: A family of optimal optical spike inference algorithms for inferring neural connectivity from population calcium imaging.) | ||||
| Carey E. Priebe | post-doc | (Robotree) | ||
BETA: Related publications
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Publications
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| Panda S, Shen C, Perry R, et al. (2024) Universally Consistent K-Sample Tests via Dependence Measures. Statistics & Probability Letters. 216 |
| Pedigo BD, Winding M, Priebe CE, et al. (2023) Bisected graph matching improves automated pairing of bilaterally homologous neurons from connectomes. Network Neuroscience (Cambridge, Mass.). 7: 522-538 |
| Pedigo BD, Powell M, Bridgeford EW, et al. (2023) Generative network modeling reveals quantitative definitions of bilateral symmetry exhibited by a whole insect brain connectome. Elife. 12 |
| Winding M, Pedigo BD, Barnes CL, et al. (2023) The connectome of an insect brain. Science (New York, N.Y.). 379: eadd9330 |
| Shen C, Panda S, Vogelstein JT. (2021) The Chi-Square Test of Distance Correlation. Journal of Computational and Graphical Statistics : a Joint Publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America. 31: 254-262 |
| Mehta K, Goldin RF, Marchette D, et al. (2021) Neuronal classification from network connectivity via adjacency spectral embedding. Network Neuroscience (Cambridge, Mass.). 5: 689-710 |
| Arroyo J, Athreya A, Cape J, et al. (2021) Inference for Multiple Heterogeneous Networks with a Common Invariant Subspace. Journal of Machine Learning Research : Jmlr. 22: 1-49 |
| Bridgeford EW, Wang S, Wang Z, et al. (2021) Eliminating accidental deviations to minimize generalization error and maximize replicability: Applications in connectomics and genomics. Plos Computational Biology. 17: e1009279 |
| Hong SJ, Xu T, Nikolaidis A, et al. (2020) Toward a Connectivity Gradient-based Framework for Reproducible Biomarker Discovery. Neuroimage. 117322 |
| Wang N, Anderson RJ, Ashbrook DG, et al. (2020) Variability and Heritability of Mouse Brain Structure: Microscopic MRI Atlases and Connectomes for Diverse Strains. Neuroimage. 117274 |