Optimal Transport, Deep Learning, Computational Geometry, Probability Distributions, Convex Optimization.
it. In short, GAN is a generative model consisting of two neural networks, one is discriminator and another is generator. The discriminator network is used to judge whether an image is “fake” or “real”, which is usually pre-trained. The generator model will generate images taking input points from