NIPS 2016 Tutorial: Generative Adversarial Networks

This report summarizes the tutorial presented by the author at NIPS 2016 on generative adversarial networks (GANs). The tutorial describes: (1) Why generative modeling is a topic worth studying, (2) how generative models work, and how GANs compare to other generative models, (3) the details of how GANs work, (4) research frontiers in GANs, and (5) state-of-the-art image models that combine GANs with other methods. Finally, the tutorial contains three exercises for readers to complete, and the solutions to these exercises.

• Publication year

  2016

• Venue

  arXiv.org

• Publication date

  2016-12-31

• Fields of study

  Mathematics, Computer Science

• Identifiers
  arXiv 1701.00160
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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