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    Safety, alignment & interpretability· 2013

    Visualizing and Understanding Convolutional Networks

    Matthew D. Zeiler (first author) · 2013 · published 2014

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    arXiv 1311.2901OpenAlex W1849277567

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    Why it matters

    Revealed learned CNN features through deconvolutional visualizations, influencing architecture design and model analysis.

    Condensed from the expert lists' notes.

    The record

    First released
    2013 (from arXiv 1311.2901)
    Published
    2014
    Citations
    17,496 citations, as counted by Papers With Code (CC BY-SA 4.0)
    Named by
    both expert lists
    Also relevant to
    Computer vision & multimodal
    Score
    0.680 · computed rank 85 · consensus 0.84, must-read 0.5, citations percentile 0.936 (2010s · safety), awards 0, existing lists 0.5. 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.