normflows: A PyTorch Package for Normalizing Flows

Understand

Normalizing flows model probability distributions through an expressive tractable density.

• They transform a simple base distribution, such as a Gaussian, through a sequence of invertible functions, which are referred to as layers.
• These layers typically use neural networks to become very expressive.
• Flows are ubiquitous in machine learning and have been applied to image generation, text modeling, variational inference, approximating Boltzmann distributions, and many other problems.