Adversarial Fisher Vectors for Unsupervised Representation Learning

Walter Talbott
Walter Talbott
Joshua Susskind
Joshua Susskind

NeurIPS, pp. 11156-11166, 2019.

Cited by: 2|Bibtex|Views73
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Other Links: dblp.uni-trier.de|arxiv.org

Abstract:

We examine Generative Adversarial Networks (GANs) through the lens of deep Energy Based Models (EBMs), with the goal of exploiting the density model that follows from this formulation. In contrast to a traditional view where the discriminator learns a constant function when reaching convergence, here we show that it can provide useful i...More

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