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    Graph learning· 2015

    Convolutional Networks on Graphs for Learning Molecular Fingerprints

    David Duvenaud (first author) · 2015

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    arXiv 1509.09292OpenAlex W2173027866

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    Why it matters

    Introduced end-to-end differentiable molecular fingerprints, influencing modern molecular graph networks.

    Condensed from the expert lists' notes.

    The record

    First released
    2015 (from arXiv 1509.09292)
    Citations
    3,719 citations, as counted by Papers With Code (CC BY-SA 4.0)
    Named by
    both expert lists
    Also relevant to
    AI for science
    Score
    0.342 · computed rank 500 · consensus 0.53, must-read 0, citations percentile 0.522 (2010s · 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.