Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures

Mohamed El Amine Seddik, Cosme Louart, Mohamed Tamaazousti, Romain Couillet

Abstract: This paper shows that deep learning (DL) representations of data produced by generative adversarial nets (GANs) are random vectors which fall within the class of so-called \emph{concentrated} rando...