Machine Learning, Deep Learning, Generative Model, Adversarial Network, Autoencoder.
some variations. But it is not always possible to learn the exact distribution of our data either implicitly or explicitly and so we try to model a distribution which is as similar as possible to the true data distribution. For this, we can leverage the power of neural networks to learn a function