Generative Models through Normalizing Flows

Normalizing flow (NF) refers to a family of generative models. Its paradigm is to transform a simple distribution into a complex distribution through a series of inversible functions. Therefore, we’re able to compute the likelihood and apply maximum likelihood learning. Generation is done through sampling from the simple distribution and transforming it with the series of function.