21 citations · 48 across the 3 of their papers we have counts for
3 papers
stat.ML2017★ 21 cited
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…
cs.LG2017★ 11 cited
Deep Graph Attention Model
John Boaz Lee, Ryan Rossi, Xiangnan Kong
Graph classification is a problem with practical applications in many different domains. Most of the existing methods take the entire graph into account when calculating graph feat…
stat.ML2017★ 16 cited
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.…