251 citations · 833 across the 13 of their papers we have counts for
4 papers · 1 filter
Towards Accurate Generative Models of Video: A New Metric & Challenges
Thomas Unterthiner, Sjoerd van Steenkiste, Karol Kurach +3
Recent advances in deep generative models have lead to remarkable progress in synthesizing high quality images. Following their successful application in image processing and repre…
Investigating Object Compositionality in Generative Adversarial Networks
Sjoerd van Steenkiste, Karol Kurach, Jürgen Schmidhuber +1
Deep generative models seek to recover the process with which the observed data was generated. They may be used to synthesize new samples or to subsequently extract representations…
A Large-Scale Study on Regularization and Normalization in GANs
Karol Kurach, Mario Lucic, Xiaohua Zhai +2
Generative adversarial networks (GANs) are a class of deep generative models which aim to learn a target distribution in an unsupervised fashion. While they were successfully appli…
MemGEN: Memory is All You Need
Sylvain Gelly, Karol Kurach, Marcin Michalski +1
We propose a new learning paradigm called Deep Memory. It has the potential to completely revolutionize the Machine Learning field. Surprisingly, this paradigm has not been reinven…