This repository compiles awesome resources covering normalizing flows, a deep learning technique for density estimation and generative modeling. It serves as a reference collection for researchers and practitioners, organizing publications, implementations, applications, and educational videos. Normalizing flows work by chaining trainable bijective transformations to transform simple base distributions into complex ones, enabling tasks like variational inference and Bayesian neural network posterior approximation.