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    Machine learning foundations· survey· 2019

    An Introduction to Variational Autoencoders

    Kingma (first author) · 2019

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    DOI 10.1561/2200000056arXiv 1906.02691OpenAlex W2948978827

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    Why it matters

    Comprehensive modern treatment of VAEs.

    Condensed from the expert lists' notes.

    The record

    First released
    2019 (from arXiv 1906.02691)
    Citations
    3,263 citations, as counted by Papers With Code (CC BY-SA 4.0)
    Named by
    the grok list only

    Editor's notes

    • Classed as survey: A tutorial by the VAE's authors; the original paper (Auto-Encoding Variational Bayes) is ranked separately. (AI draft (Claude), not yet reviewed, 2026-10-29)

    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.