21 citations · 58 across the 6 of their papers we have counts for
3 papers · 1 filter
Inductive Representation Learning in Large Attributed Graphs
Nesreen K. Ahmed, Ryan A. Rossi, Rong Zhou +4
Graphs (networks) are ubiquitous and allow us to model entities (nodes) and the dependencies (edges) between them. Learning a useful feature representation from graph data lies at…
Matrix-normal models for fMRI analysis
Michael Shvartsman, Narayanan Sundaram, Mikio C. Aoi +3
Multivariate analysis of fMRI data has benefited substantially from advances in machine learning. Most recently, a range of probabilistic latent variable models applied to fMRI dat…
A Framework for Generalizing Graph-based Representation Learning Methods
Nesreen K. Ahmed, Ryan A. Rossi, Rong Zhou +4
Random walks are at the heart of many existing deep learning algorithms for graph data. However, such algorithms have many limitations that arise from the use of random walks, e.g.…