504 citations · 2k across the 109 of their papers we have counts for
6 papers · 1 filter
Fast Approximate Quadratic Programming for Large (Brain) Graph Matching
Joshua T. Vogelstein, John M. Conroy, Vince Lyzinski +6
Quadratic assignment problems (QAPs) arise in a wide variety of domains, ranging from operations research to graph theory to computer vision to neuroscience. In the age of big data…
Shuffled Graph Classification: Theory and Connectome Applications
Joshua T. Vogelstein, Carey E. Priebe
We develop a formalism to address statistical pattern recognition of graph valued data. Of particular interest is the case of all graphs having the same number of uniquely labeled…
Magnetic Resonance Connectome Automated Pipeline
William R. Gray, John A. Bogovic, Joshua T. Vogelstein +3
This manuscript presents a novel, tightly integrated pipeline for estimating a connectome, which is a comprehensive description of the neural circuits in the brain. The pipeline ut…
Optimizing the quantity/quality trade-off in connectome inference
Carey E. Priebe, Joshua T. Vogelstein, Davi Bock
We demonstrate a meaningful prospective power analysis for an (admittedly idealized) illustrative connectome inference task. Modeling neurons as vertices and synapses as edges in a…
Graph Classification using Signal-Subgraphs: Applications in Statistical Connectomics
Joshua T. Vogelstein, William R. Gray, R. Jacob Vogelstein +1
This manuscript considers the following "graph classification" question: given a collection of graphs and associated classes, how can one predict the class of a newly observed grap…
A Bayesian approach for inferring neuronal connectivity from calcium fluorescent imaging data
Yuriy Mishchencko, Joshua T. Vogelstein, Liam Paninski
Deducing the structure of neural circuits is one of the central problems of modern neuroscience. Recently-introduced calcium fluorescent imaging methods permit experimentalists to…