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?

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