Latent Variable Models

Cycle-Consistent Adversarial Learning as Approximate Bayesian Inference

We formalize the problem of learning interdomain correspondences in the absence of paired data as Bayesian inference in a latent variable model (LVM), where one seeks the underlying hidden representations of entities from one domain as entities from …

A Tutorial on Variational Autoencoders with a Concise Keras Implementation

An in-depth practical guide to variational encoders from a probabilistic perspective.