Project Description Generative adversarial networks (GANs) have become the state of the art of unsupervised learning, bringing significant improvements to artificial intelligence applications. However, the GAN algorithm does not often converge and there is no well-developed theoretical framework for the study of its convergence. In this project, we will develop...