Generative Adversarial Network
One network generates candidates (generative) and the other evaluates them (discriminative).[3][4][5][6] Typically, the generative network learns to map from a latent space to a particular data distribution of interest, while the discriminative network discriminates between instances from the true data distribution and candidates produced by the generator. The generative network's training objective is to increase the error rate of the discriminative network
https://en.m.wikipedia.org/wiki/Generative_adversarial_network
New networks come out day by day~
