Machine Learning, Deep Learning, Generative Model, Adversarial Network, Autoencoder.
variational inference which is basically an optimization problem in Bayesian statistics. We first model P(z|X) using simpler distribution Q(z|X) which is easy to find and we try to minimize the difference between P(z|X) and Q(z|X) using KL-divergence metric approach so that our hypothesis is close