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    Generative models· 2017

    Wasserstein Generative Adversarial Networks

    Martin Arjovsky (first author) · 2017

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    arXiv 1701.07875OpenAlex W2739748921

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    Why it matters

    Replaced divergence objectives with Wasserstein distance, fundamentally improving GAN training theory.

    Condensed from the expert lists' notes.

    The record

    First released
    2017 (from arXiv 1701.07875)
    Citations
    6,382 citations, as counted by OpenAlex (CC0)
    Named by
    both expert lists
    Score
    0.484 · computed rank 248 · consensus 0.8, must-read 0.5, citations percentile 0.556 (2010s · generative-models), 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.