the open
    research
    Contribute
    Back to the reading lists

    Machine learning foundations· 2014

    Stochastic Backpropagation and Approximate Inference in Deep Generative Models

    Danilo Jimenez Rezende (first author) · 2014

    Read the original

    arXiv 1401.4082OpenAlex W1909320841

    On the reading lists

    Why it matters

    Independently developed stochastic backpropagation for scalable deep generative latent-variable models.

    Condensed from the expert lists' notes.

    The record

    First released
    2014 (from arXiv 1401.4082)
    Citations
    6,329 citations, as counted by Semantic Scholar logoSemantic Scholar (non-commercial licence)
    Named by
    the chatgpt list only
    Also relevant to
    Generative models
    Score
    0.336 · computed rank 514 · consensus 0.11, must-read 0, citations percentile 0.865 (2010s · foundations), 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.