Dive head first into advanced GANs: exploring self-attention and spectral norm

Lately, Generative Models are drawing a lot of attention. Much of that comes from Generative Adversarial Networks (GANs). Invented by Goodfellow et al, GANs are a framework in which two players compete with one another. The two actors, the generator G and discriminator D, are both represented by function approximators. Moreover, they play different roles in the game. Given a training data Dt, G creates samples as an attempt to mimic the ones from the same probability distribution as Dt.