Sylvain Gelly
Sylvain Gelly
Google Brain Zurich
Verified email at m4x.org
Title
Cited by
Cited by
Year
Combining online and offline knowledge in UCT
S Gelly, D Silver
Proceedings of the 24th international conference on Machine learning, 273-280, 2007
6982007
An image is worth 16x16 words: Transformers for image recognition at scale
A Dosovitskiy, L Beyer, A Kolesnikov, D Weissenborn, X Zhai, ...
arXiv preprint arXiv:2010.11929, 2020
6862020
Are gans created equal? a large-scale study
M Lucic, K Kurach, M Michalski, S Gelly, O Bousquet
arXiv preprint arXiv:1711.10337, 2017
6302017
Wasserstein auto-encoders
I Tolstikhin, O Bousquet, S Gelly, B Schoelkopf
arXiv preprint arXiv:1711.01558, 2017
6222017
Modification of UCT with patterns in Monte-Carlo Go
S Gelly, Y Wang, R Munos, O Teytaud
INRIA, 2006
5002006
Modification of UCT with patterns in Monte-Carlo Go
S Gelly, Y Wang, R Munos, O Teytaud
INRIA, 2006
5002006
Challenging common assumptions in the unsupervised learning of disentangled representations
F Locatello, S Bauer, M Lucic, G Raetsch, S Gelly, B Schölkopf, O Bachem
international conference on machine learning, 4114-4124, 2019
4862019
Monte-Carlo tree search and rapid action value estimation in computer Go
S Gelly, D Silver
Artificial Intelligence 175 (11), 1856-1875, 2011
3752011
Exploration exploitation in go: UCT for Monte-Carlo go
S Gelly, Y Wang
NIPS: Neural Information Processing Systems Conference On-line trading of …, 2006
2762006
Exploration exploitation in go: UCT for Monte-Carlo go
S Gelly, Y Wang
NIPS: Neural Information Processing Systems Conference On-line trading of …, 2006
2762006
The grand challenge of computer Go: Monte Carlo tree search and extensions
S Gelly, L Kocsis, M Schoenauer, M Sebag, D Silver, C Szepesvári, ...
Communications of the ACM 55 (3), 106-113, 2012
2582012
Parameter-efficient transfer learning for NLP
N Houlsby, A Giurgiu, S Jastrzebski, B Morrone, Q De Laroussilhe, ...
International Conference on Machine Learning, 2790-2799, 2019
1922019
Big transfer (bit): General visual representation learning
A Kolesnikov, L Beyer, X Zhai, J Puigcerver, J Yung, S Gelly, N Houlsby
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
1882020
Adagan: Boosting generative models
I Tolstikhin, S Gelly, O Bousquet, CJ Simon-Gabriel, B Schölkopf
arXiv preprint arXiv:1701.02386, 2017
1802017
Assessing generative models via precision and recall
MSM Sajjadi, O Bachem, M Lucic, O Bousquet, S Gelly
arXiv preprint arXiv:1806.00035, 2018
1672018
Achieving master level play in 9 x 9 computer go.
S Gelly, D Silver
AAAI 8, 1537-1540, 2008
1632008
Modifications of UCT and sequence-like simulations for Monte-Carlo Go
Y Wang, S Gelly
2007 IEEE Symposium on Computational Intelligence and Games, 175-182, 2007
1632007
On mutual information maximization for representation learning
M Tschannen, J Djolonga, PK Rubenstein, S Gelly, M Lucic
arXiv preprint arXiv:1907.13625, 2019
1532019
Episodic curiosity through reachability
N Savinov, A Raichuk, R Marinier, D Vincent, M Pollefeys, T Lillicrap, ...
arXiv preprint arXiv:1810.02274, 2018
1232018
The gan landscape: Losses, architectures, regularization, and normalization
K Kurach, M Lucic, X Zhai, M Michalski, S Gelly
1132018
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