Tom Schaul

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Coauteurs

David SilverDeepMind, UCLAdresse e-mail validée de google.com
Juergen SchmidhuberKing Abdullah University of Science and Technology / The Swiss AI Lab, IDSIA / University of LuganoAdresse e-mail validée de kaust.edu.sa
Daan WierstraPrincipal Scientist, DeepMindAdresse e-mail validée de google.com
Nando de FreitasCIFAR & DeepMindAdresse e-mail validée de google.com
Oriol VinyalsResearch Scientist at Google DeepMindAdresse e-mail validée de google.com
Tobias GlasmachersAdresse e-mail validée de idsia.ch
Will DabneyDeepMindAdresse e-mail validée de google.com
Joseph ModayilOpenmind Research Institute & Keen AGIAdresse e-mail validée de openmindresearch.org
Julian TogeliusAssociate Professor of Computer Science and Engineering, New York University; co-founder, modl.aiAdresse e-mail validée de nyu.edu
koray kavukcuogluDeepMindAdresse e-mail validée de kavukcuoglu.org
Andre BarretoResearch Scientist, Google DeepMindAdresse e-mail validée de google.com
Rémi MunosFAIR, MetaAdresse e-mail validée de inria.fr
Diana BorsaDeepMindAdresse e-mail validée de google.com
Simon OsinderoPrincipal Scientist (Director) @ DeepMindAdresse e-mail validée de google.com
Max JaderbergChief AI Officer, Isomorphic LabsAdresse e-mail validée de robots.ox.ac.uk
Simon LucasProfessor of Artificial Intelligence, Queen Mary University of LondonAdresse e-mail validée de qmul.ac.uk
Jan PetersProfessor for Intelligent Autonomous Systems/TU Darmstadt, Dept. Head/German AI Research Center DFKIAdresse e-mail validée de ias.tu-darmstadt.de
Marc G. BellemareReliant AIAdresse e-mail validée de reliant.ai
Karen SimonyanChief Scientist, Microsoft AIAdresse e-mail validée de microsoft.com
Yann LeCunChief AI Scientist at Facebook & Silver Professor at the Courant Institute, New York UniversityAdresse e-mail validée de cs.nyu.edu

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Tom Schaul

Senior Staff Scientist, DeepMind

Adresse e-mail validée de nyu.edu - Page d'accueil

Reinforcement Learning Deep Learning Deep Reinforcement Learning Game AI Exploration


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Dueling Network Architectures for Deep Reinforcement Learning Z Wang, T Schaul, M Hessel, H van Hasselt, M Lanctot, N de Freitas International Conference on Machine Learning (ICML), 2016	5527	2016
Prioritized Experience Replay T Schaul, J Quan, I Antonoglou, D Silver International Conference on Learning Representations (ICLR), 2016	5502	2016
Grandmaster level in StarCraft II using multi-agent reinforcement learning O Vinyals, I Babuschkin, WM Czarnecki, M Mathieu, A Dudzik, J Chung, ... Nature 575 (7782), 350–354, 2019	5101	2019
Rainbow: Combining Improvements in Deep Reinforcement Learning M Hessel, J Modayil, H Van Hasselt, T Schaul, G Ostrovski, W Dabney, ... AAAI Conference on Artificial Intelligence, 2018	2998	2018
Learning to learn by gradient descent by gradient descent M Andrychowicz, M Denil, S Gomez, MW Hoffman, D Pfau, T Schaul, ... Neural Information Processing Systems (NeurIPS), 2016	2522	2016
Unifying Count-Based Exploration and Intrinsic Motivation MG Bellemare, S Srinivasan, G Ostrovski, T Schaul, D Saxton, R Munos Neural Information Processing Systems (NeurIPS), 2016	1837	2016
Reinforcement learning with unsupervised auxiliary tasks M Jaderberg, V Mnih, WM Czarnecki, T Schaul, JZ Leibo, D Silver, ... International Conference on Learning Representations (ICLR), 2017	1482	2017
Deep Q-learning from Demonstrations T Hester, M Vecerik, O Pietquin, M Lanctot, T Schaul, B Piot, D Horgan, ... AAAI Conference on Artificial Intelligence, 2018	1386	2018
Universal value function approximators T Schaul, D Horgan, K Gregor, D Silver International Conference on Machine Learning (ICML-15), 1312-1320, 2015	1318	2015
StarCraft II: A New Challenge for Reinforcement Learning O Vinyals, T Ewalds, S Bartunov, P Georgiev, AS Vezhnevets, M Yeo, ... arXiv preprint arXiv:1708.04782, 2017	1210	2017
Feudal networks for hierarchical reinforcement learning AS Vezhnevets, S Osindero, T Schaul, N Heess, M Jaderberg, D Silver, ... International Conference on Machine Learning (ICML), 2017	1140	2017
Natural evolution strategies D Wierstra, T Schaul, T Glasmachers, Y Sun, J Peters, J Schmidhuber The Journal of Machine Learning Research 15 (1), 949-980, 2014	1117	2014
Successor features for transfer in reinforcement learning A Barreto, W Dabney, R Munos, JJ Hunt, T Schaul, D Silver, ... Neural Information Processing Systems (NeurIPS), 2017	707	2017
No more pesky learning rates T Schaul, S Zhang, Y LeCun International Conference on Machine Learning (ICML'13), 2013	603	2013
AlphaStar: Mastering the Real-Time Strategy Game StarCraft II O Vinyals, I Babuschkin, J Chung, M Mathieu, M Jaderberg, W Czarnecki, ... (DeepMind blog), 2019	591	2019
PyBrain T Schaul, J Bayer, D Wierstra, Y Sun, M Felder, F Sehnke, T Rückstieß, ... Journal of Machine Learning Research 11 (Feb), 743-746, 2010	487	2010
The predictron: End-to-end learning and planning D Silver, H van Hasselt, M Hessel, T Schaul, A Guez*, T Harley, ... International Conference on Machine Learning (ICML), 2017	366*	2017
AI for social good: unlocking the opportunity for positive impact N Tomašev, J Cornebise, F Hutter, S Mohamed, A Picciariello, B Connelly, ... Nature Communications 11 (2468), 1-6, 2020	313	2020
The 2014 General Video Game Playing Competition D Perez, S Samothrakis, J Togelius, T Schaul, S Lucas, A Couëtoux, ... Computational Intelligence and AI in Games, 2015	289*	2015
A video game description language for model-based or interactive learning T Schaul Conference on Computational Intelligence in Games (IEEE-CIG), 1-8, 2013	288	2013

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