GEMS Lab: Graph Exploration & Mining at Scale, University of Michigan

Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)

GemsLab

Representation learning-based graph alignment based on implicit matrix factorization and structural embeddings

GemsLab

GemsLab

Knowledge Graph summarization for anomaly/error detection & completion (WebConf '20)

GemsLab

Slides and code for the Morgan Claypool book on "Individual and Collective Graph Mining: Principles, Algorithms and Applications"

GemsLab

Summarization of static graphs using the Minimum Description Length principle

GemsLab

The SEMB library is an easy-to-use tool for getting and evaluating structural node embeddings in graphs.

GemsLab