Methods › Computer Vision › Generative Adversarial Networks › PresGAN
Prescribed Generative Adversarial Network
PresGAN
Introduced by Adji B. Dieng et al. in Prescribed Generative Adversarial Networks
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Prescribed GANs add noise to the output of a density network and optimize an entropy-regularized adversarial loss. The added noise renders tractable approximations of the predictive log-likelihood and stabilizes the training procedure. The entropy regularizer encourages PresGANs to capture all the modes of the data distribution. Fitting PresGANs involves computing the intractable gradients of the entropy regularization term; PresGANs sidestep this intractability using unbiased stochastic estimates.
Papers archive 2025-07-28
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Prescribed Generative Adversarial Networks 9 Oct 2019 · 2 repositories · arXiv:1910.04302
Tasks archive 2025-07-28
1 task the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Image Generation | 1 |
Usage over time archive 2025-07-28
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Categories archive 2025-07-28
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