On optimal solutions of classical and sliced Wasserstein GANs with non-Gaussian data

Yu-Jui Huang, Hsin-Hua Shen, Yu-Chih Huang +2

The generative adversarial network (GAN) aims to approximate an unknown distribution via a parameterized neural network (NN). While GANs have been widely applied in reinforcement a…