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Karol Kurach

2 accepted papers

2019

A Large-Scale Study on Regularization and Normalization in GANs

ICML 2019oral

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 applied to many problems, training a GAN is a notoriously challenging task and requires a significant number of hyperparamete…

2018

Are GANs Created Equal? A Large-Scale Study

NeurIPS 2018poster

Generative adversarial networks (GAN) are a powerful subclass of generative models. Despite a very rich research activity leading to numerous interesting GAN algorithms, it is still very hard to assess which algorithm(s) perform better than others. We conduct a neutral, multi-faceted large-scale em…