the open
    research
    Contribute
    Back to the reading lists

    Graph learning· 2018

    Hierarchical Graph Representation Learning with Differentiable Pooling

    Rex Ying (first author) · 2018

    Read the original

    arXiv 1806.08804OpenAlex W2811124557

    On the reading lists

    Why it matters

    Introduced trainable hierarchical graph coarsening through differentiable cluster assignments.

    Condensed from the expert lists' notes.

    The record

    First released
    2018 (from arXiv 1806.08804)
    Citations
    2,640 citations, as counted by Semantic Scholar logoSemantic Scholar (non-commercial licence)
    Named by
    both expert lists
    Score
    0.358 · computed rank 459 · consensus 0.61, must-read 0, citations percentile 0.5 (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), and Semantic Scholar logoSemantic Scholar (used under its non-commercial API licence). Each count names its source. See the method.