May 9, 2021

VAEs as a framework for probabilistic inference

VAEs frequently get compared to GANs, and then dismissed since “GANs produce better samples”. While this might be true for specific VAEs, I think this sells VAEs short. Do I claim that VAEs generate better samples of imaginary celebrities? No (but they are also pretty good). What I mean is that they are qualitatively different and much more general than people give them credit. In this article we are going to consider VAEs as a family of latent variable models and discover that they offer a unified black-box inference framework for probabilistic modelling. Read more

© Sebastian Callh 2020