4 papers
Generative models with kernel distance in data space
Szymon Knop, Marcin Mazur, Przemysław Spurek +2
Generative models dealing with modeling a~joint data distribution are generally either autoencoder or GAN based. Both have their pros and cons, generating blurry images or being un…
One-element Batch Training by Moving Window
Przemysław Spurek, Szymon Knop, Jacek Tabor +2
Several deep models, esp. the generative, compare the samples from two distributions (e.g. WAE like AutoEncoder models, set-processing deep networks, etc) in their cost functions.…
Sliced generative models
Szymon Knop, Marcin Mazur, Jacek Tabor +2
In this paper we discuss a class of AutoEncoder based generative models based on one dimensional sliced approach. The idea is based on the reduction of the discrimination between s…
Cramer-Wold AutoEncoder
Szymon Knop, Jacek Tabor, Przemysław Spurek +3
We propose a new generative model, Cramer-Wold Autoencoder (CWAE). Following WAE, we directly encourage normality of the latent space. Our paper uses also the recent idea from Slic…