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Generative Adversarial Nets

Generative adversarial nets (GANs) are a class of deep learning models that consist of two neural networks: a generator and a discriminator.

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Cite this as

Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio (2024). Dataset: Generative Adversarial Nets. https://doi.org/10.57702/o0ovij16

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Additional Info

Field Value
Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.1811.11212
Citation
  • https://doi.org/10.48550/arXiv.2110.03875
  • https://doi.org/10.48550/arXiv.2210.12100
  • https://doi.org/10.48550/arXiv.2303.13495
Author Ian Goodfellow
More Authors
Jean Pouget-Abadie
Mehdi Mirza
Bing Xu
David Warde-Farley
Sherjil Ozair
Aaron Courville
Yoshua Bengio
Homepage https://arxiv.org/abs/1406.2661