You are all cordially invited to the AMLab seminar on **Tuesday February 14 at 16:00 in C3.163**, where** Jakub Tomczak** will give a talk titled “**Improving Variational Auto-Encoders using volume-preserving flows: A preliminary study”**. Afterwards there are the usual drinks and snacks!

**Abstract**: Variational auto-encoders (VAE) are scalable and powerful generative models. However, the choice of the variational posterior determines tractability and flexibility of the VAE. Commonly, latent variables are modeled using the normal distribution with a diagonal covariance matrix. This results in computational efficiency but typically it is not flexible enough to match the true posterior distribution. One fashion of enriching the variational posterior distribution is application of normalizing flows, i.e., a series of invertible transformations to latent variables with a simple posterior. Application of general normalizing flows requires calculating the Jacobian-determinant that could be computationally troublesome. However, it is possible to design a series of transformations for which the Jacobian-determinant equals 1, so called volume-preserving flows. During the presentation I will describe my preliminary results on new volume-preserving flow called Householder flow and an extension of the linear Inverse Autoregressive Flow.