Historical context & research account
GANs organize generation through learning data distributions. In contrast with a rule-based system such as AARON, the logic producing an image is learned from training data rather than mainly being specified by an artist. The master identifies a change in how machine images are understood: outputs are treated as samples from a learned distribution.
Dates & version record
Date displayed for this node：2014 · Date recorded in the research master：2014
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Original sources & further reading
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Generative Adversarial Nets
https://papers.nips.cc/paper/5423-generative-adversarial-nets
Current cited URL
Provenance, translation & verification
Archive node #045 · Historical node
Research masters & supplement references · 1
AI Art Genealogy Research Master · p. 15 · 045
Date as recorded: 2014
Generative Adversarial Nets ↗
Generative Adversarial Nets
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Cite this node
ANTI-AI ARCHIVE. Generative Adversarial Nets. Art-history node #045. https://salondesrefuses.cn/en/art-history/045
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