79 citations · 289 across the 9 of their papers we have counts for
9 papers
On Proximity and Structural Role-based Embeddings in Networks: Misconceptions, Techniques, and Applications
Ryan A. Rossi, Di Jin, Sungchul Kim +3
Structural roles define sets of structurally similar nodes that are more similar to nodes inside the set than outside, whereas communities define sets of nodes with more connection…
Dynamic Node Embeddings from Edge Streams
John Boaz Lee, Giang Nguyen, Ryan A. Rossi +3
Networks evolve continuously over time with the addition, deletion, and changing of links and nodes. Such temporal networks (or edge streams) consist of a sequence of timestamped e…
Higher-order Graph Convolutional Networks
John Boaz Lee, Ryan A. Rossi, Xiangnan Kong +3
Following the success of deep convolutional networks in various vision and speech related tasks, researchers have started investigating generalizations of the well-known technique…
Attention Models in Graphs: A Survey
John Boaz Lee, Ryan A. Rossi, Sungchul Kim +2
Graph-structured data arise naturally in many different application domains. By representing data as graphs, we can capture entities (i.e., nodes) as well as their relationships (i…
Learning Role-based Graph Embeddings
Nesreen K. Ahmed, Ryan Rossi, John Boaz Lee +4
Random walks are at the heart of many existing network embedding methods. However, such algorithms have many limitations that arise from the use of random walks, e.g., the features…
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…