Machine Learning, Deep Learning, Generative Model, Adversarial Network, Autoencoder.
Discriminator. The idea is to sample from a simple distribution like Gaussian and then learn to transform this noise to data distribution using universal function approximators such as neural networks. This is achieved by adversarial training of these two networks. A generator model G learns to