This document discusses Generative Adversarial Networks (GANs). GANs use two neural networks, a generator and a discriminator, that compete against each other. The generator learns to generate new data with the same statistics as the training set while the discriminator learns to determine whether samples are from the generator or the training set. They are trained using an objective function that pits the generator and discriminator against each other until the generator fools the discriminator consistently.