GAN (Generative Adversarial Network)

Ian Goodfellow, 2014

Introduced by Ian Goodfellow in 2014, Generative Adversarial Networks pit a Generator against a Discriminator in a minimax game. The Generator learns to produce realistic data from random noise, while the Discriminator learns to tell real data from fakes. The visualization shows the adversarial loop: noise flows through the Generator to produce a sample, the Discriminator judges it, and gradient feedback flows back to improve the Generator over successive iterations.