Deep Learning, Generative Adversarial Networks & Boxing – Toward a Fundamental Understanding

A generative adversarial network (GAN) is composed of two separate networks - the generator and the discriminator. It poses the unsupervised learning problem as a game between the two. In this post we will see why GANs have so much potential, and frame GANs as a boxing match between two opponents. Deep learning is famously biologically inspired and many of the major concepts in deep learning are intuitive and grounded in reality. The fundamental truth of deep learning is that it's hierarchical -- the layers in a network and the representations they learn build on each other.