Generative Modeling

A complete guide to implementing modern Variational Autoencoders in PyTorch. Includes a copy-pasteable implementation, explanation of KL annealing to fix posterior collapse, and a deep dive into stable standard deviation parameterizations.

An in-depth guide to GANs: how two neural networks compete to generate realistic data, the math behind it, and the evolution of objective functions that stabilize training.