Generative Adversarial Networks (GAN) Review

Abstract

Latest research in Deep Learning Networks (DLN), the frontier of machine versus human, is making fast strides into harder problems of learning and cognition. Generative Adversarial networks (GAN) are the state of the art learning networks showing promise in this direction. GANs are actively researched and pursued both in academics as well as business enterprises. An understanding of this new machine learning technique (GANs) and their possible usages are discussed in
this paper. Results from a representative problem of one dimensional data are presented.