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ORCIDKarol Kurach
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2020 – today
- 2020
[j2]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: 102921 (2020)- [j1]Sjoerd van Steenkiste, Karol Kurach, Jürgen Schmidhuber, Sylvain Gelly:
Investigating object compositionality in Generative Adversarial Networks. Neural Networks 130: 309-325 (2020) - [c12]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: 4501-4510
2010 – 2019
- 2019
- [c11]Thomas Unterthiner, Sjoerd van Steenkiste, Karol Kurach, Raphaël Marinier, Marcin Michalski, Sylvain Gelly:
FVD: A new Metric for Video Generation. DGS@ICLR 2019 - [c10]Karol Kurach, Mario Lucic, Xiaohua Zhai, Marcin Michalski, Sylvain Gelly:
A Large-Scale Study on Regularization and Normalization in GANs. ICML 2019: 3581-3590 - [i14]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 abs/1907.11180 (2019) - 2018
- [c9]Mario Lucic, Karol Kurach, Marcin Michalski, Sylvain Gelly, Olivier Bousquet:
Are GANs Created Equal? A Large-Scale Study. NeurIPS 2018: 698-707 - [i13]Sylvain Gelly, Karol Kurach, Marcin Michalski, Xiaohua Zhai:
MemGEN: Memory is All You Need. CoRR abs/1803.11203 (2018) - [i12]Karol Kurach, Mario Lucic, Xiaohua Zhai, Marcin Michalski, Sylvain Gelly:
The GAN Landscape: Losses, Architectures, Regularization, and Normalization. CoRR abs/1807.04720 (2018) - [i11]Sjoerd van Steenkiste, Karol Kurach, Sylvain Gelly:
A Case for Object Compositionality in Deep Generative Models of Images. CoRR abs/1810.10340 (2018) - [i10]Thomas Unterthiner, Sjoerd van Steenkiste, Karol Kurach, Raphaël Marinier, Marcin Michalski, Sylvain Gelly:
Towards Accurate Generative Models of Video: A New Metric & Challenges. CoRR abs/1812.01717 (2018) - 2017
- [i9]Karol Kurach, Sylvain Gelly, Michal Jastrzebski, Philip Häusser, Olivier Teytaud, Damien Vincent, Olivier Bousquet:
Better Text Understanding Through Image-To-Text Transfer. CoRR abs/1705.08386 (2017) - [i8]Olivier Bousquet, Sylvain Gelly, Karol Kurach, Marc Schoenauer, Michèle Sebag, Olivier Teytaud, Damien Vincent:
Toward Optimal Run Racing: Application to Deep Learning Calibration. CoRR abs/1706.03199 (2017) - [i7]Olivier Bousquet, Sylvain Gelly, Karol Kurach, Olivier Teytaud, Damien Vincent:
Critical Hyper-Parameters: No Random, No Cry. CoRR abs/1706.03200 (2017) - [i6]Mario Lucic, Karol Kurach, Marcin Michalski, Sylvain Gelly, Olivier Bousquet:
Are GANs Created Equal? A Large-Scale Study. CoRR abs/1711.10337 (2017) - 2016
- [c8]Karol Kurach, Krzysztof Pawlowski:
Predicting Dangerous Seismic Activity with Recurrent Neural Networks. FedCSIS 2016: 239-243 - [c7]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: 955-964 - [c6]Karol Kurach, Marcin Andrychowicz, Ilya Sutskever:
Neural Random-Access Machines. ICLR (Poster) 2016 - [i5]Marcin Andrychowicz, Karol Kurach:
Learning Efficient Algorithms with Hierarchical Attentive Memory. CoRR abs/1602.03218 (2016) - [i4]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 abs/1606.04870 (2016) - [i3]Karol Kurach, Marcin Andrychowicz, Ilya Sutskever:
Neural Random Access Machines. ERCIM News 2016(107) (2016) - 2015
- [c5]Karol Kurach, Krzysztof Pawlowski:
Detecting Hazardous Events from Sequential Data with Multilayer Architectures. CS&P 2015: 1-10 - [c4]Krzysztof Pawlowski, Karol Kurach:
Detecting Methane Outbreaks from Time Series Data with Deep Neural Networks. RSFDGrC 2015: 475-484 - [i2]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 abs/1511.06807 (2015) - 2014
- [c3]Krzysztof Pawlowski, Karol Kurach, Kim Svensson, Sarvapali D. Ramchurn, Tomasz P. Michalak, Talal Rahwan:
Coalition structure generation with the graphics processing unit. AAMAS 2014: 293-300 - [c2]Wojciech Zaremba, Karol Kurach, Rob Fergus:
Learning to Discover Efficient Mathematical Identities. NIPS 2014: 1278-1286 - [i1]Wojciech Zaremba, Karol Kurach, Rob Fergus:
Learning to Discover Efficient Mathematical Identities. CoRR abs/1406.1584 (2014) - 2013
- [p1]Karol Kurach, Krzysztof Pawlowski, Lukasz Romaszko, Marcin Tatjewski, Andrzej Janusz, Hung Son Nguyen:
Multi-label Classification of Biomedical Articles. Intelligent Tools for Building a Scientific Information Platform 2013: 199-214 - 2012
- [c1]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: 306-317
Coauthor Index
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