Topics On Generative Models In Machine Learning

This article discusses the use of latent variable models in machine learning, specifically in combination with neural networks and back propagation. It includes four papers that cover topics such as sample generation, clustering, disentanglement, and interpolation. The papers also introduce new methods for stochastic interpolation and adapt the Infinite Swapping algorithm to the Restricted Boltzmann Machine model.