Variational Autoencoders: theory, implementation and unanswered questions

Cédric Beaulac

In this short manuscript we introduce the Variational Autoencoder model as an extension of the well-known Gaussian Mixture Model. Various implementations of VAEs are introduced and we discuss the gap between the theory motivating the models and these implementations.

Update I am currently investing a lot of time on this project recently; it is reworked as a review of VAEs proposed improvement upon the problems of simple VAES. I will post a new version on the web site soon enough.

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