Tom Schaul

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David SilverDeepMind, UCLDirección de correo verificada de google.com
Juergen SchmidhuberKing Abdullah University of Science and Technology / The Swiss AI Lab, IDSIA / University of LuganoDirección de correo verificada de kaust.edu.sa
Daan WierstraPrincipal Scientist, DeepMindDirección de correo verificada de google.com
Nando de FreitasCIFAR & DeepMindDirección de correo verificada de google.com
Oriol VinyalsResearch Scientist at Google DeepMindDirección de correo verificada de google.com
Will DabneyDeepMindDirección de correo verificada de google.com
Tobias GlasmachersDirección de correo verificada de idsia.ch
Joseph ModayilOpenmind Research Institute & Keen AGIDirección de correo verificada de openmindresearch.org
Andre BarretoResearch Scientist, Google DeepMindDirección de correo verificada de google.com
Julian TogeliusAssociate Professor of Computer Science and Engineering, New York University; co-founder, modl.aiDirección de correo verificada de nyu.edu
koray kavukcuogluDeepMindDirección de correo verificada de kavukcuoglu.org
Rémi MunosFAIR, MetaDirección de correo verificada de inria.fr
Diana BorsaDeepMindDirección de correo verificada de google.com
Simon OsinderoPrincipal Scientist (Director) @ DeepMindDirección de correo verificada de google.com
Max JaderbergChief AI Officer, Isomorphic LabsDirección de correo verificada de robots.ox.ac.uk
Simon LucasProfessor of Artificial Intelligence, Queen Mary University of LondonDirección de correo verificada de qmul.ac.uk
Jan PetersProfessor for Intelligent Autonomous Systems/TU Darmstadt, Dept. Head/German AI Research Center DFKIDirección de correo verificada de ias.tu-darmstadt.de
Marc G. BellemareReliant AIDirección de correo verificada de reliant.ai
Karen SimonyanChief Scientist, Microsoft AIDirección de correo verificada de microsoft.com
Yann LeCunChief AI Scientist at Facebook & Silver Professor at the Courant Institute, New York UniversityDirección de correo verificada de cs.nyu.edu

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Tom Schaul

Senior Staff Scientist, DeepMind

Dirección de correo verificada de nyu.edu - Página principal

Reinforcement Learning Deep Learning Deep Reinforcement Learning Game AI Exploration


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
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	5551	2016
Prioritized Experience Replay T Schaul, J Quan, I Antonoglou, D Silver International Conference on Learning Representations (ICLR), 2016	5517	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	5119	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	3009	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	2529	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	1845	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	1391	2018
Universal value function approximators T Schaul, D Horgan, K Gregor, D Silver International Conference on Machine Learning (ICML-15), 1312-1320, 2015	1323	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	1216	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	1145	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	1121	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	699	2017
No more pesky learning rates T Schaul, S Zhang, Y LeCun International Conference on Machine Learning (ICML'13), 2013	606	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	590	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	488	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	365*	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	317	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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