TITLE: Mathematics of GANs (generative adversarial networks)
QUESTION [7 upvotes]: Generative Adversarial Networks were introduced in http://papers.nips.cc/paper/5423-generative-adversarial-nets and has more than 20000 citations.
The paper introduced key paradigm changes which require applications from modern areas of mathematics. I wanted to ask what are some the mathematics required to understand GANs as far as we know now and what are some key resources which provide accessible insight and a roadmap to learning?

REPLY [6 votes]: I recommend some papers by Lars Mescheder:

The paper The Numerics of GANs formalizes GANs as two-player games and analyzes their training dynamics,
the paper Which Training Methods for GANs do actually Converge? takes this analysis further and
the PhD thesis Stability and Expressiveness of Deep Generative Models cantains a quite thorough and mathematical introduction to GANs.