Karol Kurach

Publication Activity (10 Years)

Years Active: 2012-2020
Publications (10 Years): 24

Top Topics

Text Understanding

Generative Model

Top Venues

Publications

Maciej Zamorski, Maciej Zieba, Piotr Klukowski, Rafal Nowak, Karol Kurach, Wojciech Stokowiec, Tomasz Trzcinski
Adversarial autoencoders for compact representations of 3D point clouds. Comput. Vis. Image Underst. 193 (2020)
Sjoerd van Steenkiste, Karol Kurach, Jürgen Schmidhuber, Sylvain Gelly
Investigating object compositionality in Generative Adversarial Networks. Neural Networks 130 (2020)
Karol Kurach, Anton Raichuk, Piotr Stanczyk, Michal Zajac, Olivier Bachem, Lasse Espeholt, Carlos Riquelme, Damien Vincent, Marcin Michalski, Olivier Bousquet, Sylvain Gelly
Google Research Football: A Novel Reinforcement Learning Environment. AAAI (2020)
Karol Kurach, Mario Lucic, Xiaohua Zhai, Marcin Michalski, Sylvain Gelly
A Large-Scale Study on Regularization and Normalization in GANs. ICML (2019)
Thomas Unterthiner, Sjoerd van Steenkiste, Karol Kurach, Raphaël Marinier, Marcin Michalski, Sylvain Gelly
FVD: A new Metric for Video Generation. DGS@ICLR (2019)
Karol Kurach, Anton Raichuk, Piotr Stanczyk, Michal Zajac, Olivier Bachem, Lasse Espeholt, Carlos Riquelme, Damien Vincent, Marcin Michalski, Olivier Bousquet, Sylvain Gelly
Google Research Football: A Novel Reinforcement Learning Environment. CoRR (2019)
Mario Lucic, Karol Kurach, Marcin Michalski, Sylvain Gelly, Olivier Bousquet
Are GANs Created Equal? A Large-Scale Study. NeurIPS (2018)
Sylvain Gelly, Karol Kurach, Marcin Michalski, Xiaohua Zhai
MemGEN: Memory is All You Need. CoRR (2018)
Karol Kurach, Mario Lucic, Xiaohua Zhai, Marcin Michalski, Sylvain Gelly
The GAN Landscape: Losses, Architectures, Regularization, and Normalization. CoRR (2018)
Thomas Unterthiner, Sjoerd van Steenkiste, Karol Kurach, Raphaël Marinier, Marcin Michalski, Sylvain Gelly
Towards Accurate Generative Models of Video: A New Metric & Challenges. CoRR (2018)
Sjoerd van Steenkiste, Karol Kurach, Sylvain Gelly
A Case for Object Compositionality in Deep Generative Models of Images. CoRR (2018)
Olivier Bousquet, Sylvain Gelly, Karol Kurach, Marc Schoenauer, Michèle Sebag, Olivier Teytaud, Damien Vincent
Toward Optimal Run Racing: Application to Deep Learning Calibration. CoRR (2017)
Karol Kurach, Sylvain Gelly, Michal Jastrzebski, Philip Häusser, Olivier Teytaud, Damien Vincent, Olivier Bousquet
Better Text Understanding Through Image-To-Text Transfer. CoRR (2017)
Olivier Bousquet, Sylvain Gelly, Karol Kurach, Olivier Teytaud, Damien Vincent
Critical Hyper-Parameters: No Random, No Cry. CoRR (2017)
Mario Lucic, Karol Kurach, Marcin Michalski, Sylvain Gelly, Olivier Bousquet
Are GANs Created Equal? A Large-Scale Study. CoRR (2017)
Karol Kurach, Marcin Andrychowicz, Ilya Sutskever
Neural Random Access Machines. ERCIM News 2016 (107) (2016)
Marcin Andrychowicz, Karol Kurach
Learning Efficient Algorithms with Hierarchical Attentive Memory. CoRR (2016)
Karol Kurach, Krzysztof Pawlowski
Predicting Dangerous Seismic Activity with Recurrent Neural Networks. FedCSIS (2016)
Anjuli Kannan, Karol Kurach, Sujith Ravi, Tobias Kaufmann, Andrew Tomkins, Balint Miklos, Greg Corrado, László Lukács, Marina Ganea, Peter Young, Vivek Ramavajjala
Smart Reply: Automated Response Suggestion for Email. KDD (2016)
Karol Kurach, Marcin Andrychowicz, Ilya Sutskever
Neural Random-Access Machines. ICLR (Poster) (2016)
Anjuli Kannan, Karol Kurach, Sujith Ravi, Tobias Kaufmann, Andrew Tomkins, Balint Miklos, Greg Corrado, László Lukács, Marina Ganea, Peter Young, Vivek Ramavajjala
Smart Reply: Automated Response Suggestion for Email. CoRR (2016)
Arvind Neelakantan, Luke Vilnis, Quoc V. Le, Ilya Sutskever, Lukasz Kaiser, Karol Kurach, James Martens
Adding Gradient Noise Improves Learning for Very Deep Networks. CoRR (2015)
Karol Kurach, Krzysztof Pawlowski
Detecting Hazardous Events from Sequential Data with Multilayer Architectures. CS&P (2015)
Krzysztof Pawlowski, Karol Kurach
Detecting Methane Outbreaks from Time Series Data with Deep Neural Networks. RSFDGrC (2015)
Wojciech Zaremba, Karol Kurach, Rob Fergus
Learning to Discover Efficient Mathematical Identities. CoRR (2014)
Wojciech Zaremba, Karol Kurach, Rob Fergus
Learning to Discover Efficient Mathematical Identities. NIPS (2014)
Krzysztof Pawlowski, Karol Kurach, Kim Svensson, Sarvapali D. Ramchurn, Tomasz P. Michalak, Talal Rahwan
Coalition structure generation with the graphics processing unit. AAMAS (2014)
Karol Kurach, Krzysztof Pawlowski, Lukasz Romaszko, Marcin Tatjewski, Andrzej Janusz, Hung Son Nguyen
An Ensemble Approach to Multi-label Classification of Textual Data. ADMA (2012)