Statistical inference on random dot product graphs: a survey
The random dot product graph (RDPG) is an independent-edge random graph that is
analytically tractable and, simultaneously, either encompasses or can successfully …
analytically tractable and, simultaneously, either encompasses or can successfully …
Fast approximate quadratic programming for graph matching
Quadratic assignment problems arise in a wide variety of domains, spanning operations
research, graph theory, computer vision, and neuroscience, to name a few. The graph …
research, graph theory, computer vision, and neuroscience, to name a few. The graph …
DeltaCon Principled Massive-Graph Similarity Function with Attribution
How much has a network changed since yesterday? How different is the wiring of Bob's
brain (a left-handed male) and Alice's brain (a right-handed female), and how is it different …
brain (a left-handed male) and Alice's brain (a right-handed female), and how is it different …
Nonparametric Bayes modeling of populations of networks
Replicated network data are increasingly available in many research fields. For example, in
connectomic applications, interconnections among brain regions are collected for each …
connectomic applications, interconnections among brain regions are collected for each …
Map** population-based structural connectomes
Advances in understanding the structural connectomes of human brain require improved
approaches for the construction, comparison and integration of high-dimensional whole …
approaches for the construction, comparison and integration of high-dimensional whole …
Bayesian inference and testing of group differences in brain networks
Bayesian Inference and Testing of Group Differences in Brain Networks Page 1 Bayesian Analysis
(2018) 13, Number 1, pp. 29–58 Bayesian Inference and Testing of Group Differences in Brain …
(2018) 13, Number 1, pp. 29–58 Bayesian Inference and Testing of Group Differences in Brain …
A semiparametric two-sample hypothesis testing problem for random graphs
Two-sample hypothesis testing for random graphs arises naturally in neuroscience, social
networks, and machine learning. In this article, we consider a semiparametric problem of two …
networks, and machine learning. In this article, we consider a semiparametric problem of two …
Supervised dimensionality reduction for big data
To solve key biomedical problems, experimentalists now routinely measure millions or
billions of features (dimensions) per sample, with the hope that data science techniques will …
billions of features (dimensions) per sample, with the hope that data science techniques will …
Critical synchronization dynamics of the Kuramoto model on connectome and small world graphs
The hypothesis, that cortical dynamics operates near criticality also suggests, that it exhibits
universal critical exponents which marks the Kuramoto equation, a fundamental model for …
universal critical exponents which marks the Kuramoto equation, a fundamental model for …
Navigable maps of structural brain networks across species
Connectomes are spatially embedded networks whose architecture has been shaped by
physical constraints and communication needs throughout evolution. Using a decentralized …
physical constraints and communication needs throughout evolution. Using a decentralized …