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

Code repository for work by the GEMS Lab:


  1. REGAL Public

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

    Python 74 15

  2. Summarization of static graphs using the Minimum Description Length principle

    Python 24 17

  3. MultiLENS Public

    Framework for latent network summarization: bridging network embedding and summarization

    Python 11 2

  4. KGist Public

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

    Python 19 5

  5. GroupINN Public

    GNN with summarization/grouping layer for speed and interpretability

    Python 11 4

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

    18 9


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