Stochastic Backpropagation and Approximate Inference in Deep Generative Models

Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra

Abstract: We marry ideas from deep neural networks and approximate Bayesian inference to derive a generalised class of deep, directed generative models, endowed with a new algorithm for scalable inference an...