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    Graph learning· 2021

    Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

    Michael M. Bronstein (first author) · 2021

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    arXiv 2104.13478OpenAlex W3157286395

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    Why it matters

    Unified geometric learning architectures through symmetry, invariance, and equivariance.

    Condensed from the expert lists' notes.

    The record

    First released
    2021 (from arXiv 2104.13478)
    Citations
    1,797 citations, as counted by Papers With Code (CC BY-SA 4.0)
    Named by
    the chatgpt list only
    Score
    0.413 · computed rank 349 · consensus 0.37, must-read 0, citations percentile 0.864 (2020s · graphs), awards 0, existing lists 0. Method

    Data sources

    Catalogue data from OpenAlex (CC0), Crossref (CC0 metadata; no abstracts are shown), arXiv, and Papers With Code (CC BY-SA 4.0). Each count names its source. See the method.