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[R] Open Questions about Generative Adversarial Networks

New distill.pub article about future direction of GAN research

Open Questions about Generative Adversarial Networks

What we’d like to find out about GANs that we don’t know yet.

  1. What are the trade-offs between GANs and other generative models?

  2. What sorts of distributions can GANs model?

  3. How can we Scale GANs beyond image synthesis?

  4. What can we say about the global convergence of the training dynamics?

  5. How should we evaluate GANs and when should we use them?

  6. How does GAN training scale with batch size?

  7. What is the relationship between GANs and adversarial examples?

https://distill.pub/2019/gan-open-problems/

submitted by /u/hardmaru
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.