The document contains several links to papers and slides about generative adversarial networks (GANs). GANs use two neural networks, a generator and discriminator, that compete against each other in a game theoretic framework. The generator learns to generate new data with the same statistics as the training set to fool the discriminator, while the discriminator learns to determine whether samples are real or generated.