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Picture for Karol Kurach

Google Research Football: A Novel Reinforcement Learning Environment


Jul 25, 2019
Karol Kurach, Anton Raichuk, Piotr Stańczyk, Michał Zając, Olivier Bachem, Lasse Espeholt, Carlos Riquelme, Damien Vincent, Marcin Michalski, Olivier Bousquet, Sylvain Gelly


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Towards Accurate Generative Models of Video: A New Metric & Challenges


Dec 03, 2018
Thomas Unterthiner, Sjoerd van Steenkiste, Karol Kurach, Raphael Marinier, Marcin Michalski, Sylvain Gelly


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Are GANs Created Equal? A Large-Scale Study


Oct 29, 2018
Mario Lucic, Karol Kurach, Marcin Michalski, Sylvain Gelly, Olivier Bousquet

* NIPS'18: Added a section on the limitations of the study and additional empirical results 

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The GAN Landscape: Losses, Architectures, Regularization, and Normalization


Oct 26, 2018
Karol Kurach, Mario Lucic, Xiaohua Zhai, Marcin Michalski, Sylvain Gelly

* Changed formatting from ICML workshop to ICLR. We added additional resnet ablation studies, hinge loss, and an empirical comparison between KID and FID 

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A Case for Object Compositionality in Deep Generative Models of Images


Oct 17, 2018
Sjoerd van Steenkiste, Karol Kurach, Sylvain Gelly


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MemGEN: Memory is All You Need


Mar 29, 2018
Sylvain Gelly, Karol Kurach, Marcin Michalski, Xiaohua Zhai


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Toward Optimal Run Racing: Application to Deep Learning Calibration


Jun 20, 2017
Olivier Bousquet, Sylvain Gelly, Karol Kurach, Marc Schoenauer, Michele Sebag, Olivier Teytaud, Damien Vincent


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Critical Hyper-Parameters: No Random, No Cry


Jun 10, 2017
Olivier Bousquet, Sylvain Gelly, Karol Kurach, Olivier Teytaud, Damien Vincent


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Better Text Understanding Through Image-To-Text Transfer


May 26, 2017
Karol Kurach, Sylvain Gelly, Michal Jastrzebski, Philip Haeusser, Olivier Teytaud, Damien Vincent, Olivier Bousquet


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Smart Reply: Automated Response Suggestion for Email


Jun 15, 2016
Anjuli Kannan, Karol Kurach, Sujith Ravi, Tobias Kaufmann, Andrew Tomkins, Balint Miklos, Greg Corrado, Laszlo Lukacs, Marina Ganea, Peter Young, Vivek Ramavajjala

* Accepted to KDD 2016 

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Learning Efficient Algorithms with Hierarchical Attentive Memory


Feb 23, 2016
Marcin Andrychowicz, Karol Kurach

* Added soft attention appendix 

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Neural Random-Access Machines


Feb 09, 2016
Karol Kurach, Marcin Andrychowicz, Ilya Sutskever

* ICLR submission, 17 pages, 9 figures, 6 tables (with bibliography and appendix) 

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Adding Gradient Noise Improves Learning for Very Deep Networks


Nov 21, 2015
Arvind Neelakantan, Luke Vilnis, Quoc V. Le, Ilya Sutskever, Lukasz Kaiser, Karol Kurach, James Martens


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Learning to Discover Efficient Mathematical Identities


Nov 06, 2014
Wojciech Zaremba, Karol Kurach, Rob Fergus


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