Timothy P. Lillicrap

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David SilverGoogle DeepMindDirección de correo verificada de google.com
Adam SantoroDeepMindDirección de correo verificada de google.com
Arthur GuezGoogle DeepMindDirección de correo verificada de google.com
Jonathan J HuntTwitterDirección de correo verificada de me.net.nz
Yuval TassaResearch Scientist, Google DeepMindDirección de correo verificada de google.com
Tom ErezResearcher, DeepMindDirección de correo verificada de google.com
koray kavukcuogluDeepMindDirección de correo verificada de kavukcuoglu.org
Alexander PritzelDeepmindDirección de correo verificada de google.com
Sergey LevineUC Berkeley, GoogleDirección de correo verificada de eecs.berkeley.edu
Sergey BartunovDeepMindDirección de correo verificada de google.com
Ilya SutskeverCo-Founder and Chief Scientist of OpenAIDirección de correo verificada de openai.com
Shixiang Shane Gu (顾世翔)Senior Research Scientist, Google BrainDirección de correo verificada de google.com
Chris J. MaddisonUniversity of TorontoDirección de correo verificada de cs.toronto.edu
Alex GravesUniversity of TorontoDirección de correo verificada de cs.toronto.edu
Blake RichardsAssistant Professor, McGill UniversityDirección de correo verificada de mcgill.ca
Daniel CowndenResearch Fellow, University of St AndrewsDirección de correo verificada de st-andrews.ac.uk
Colin AkermanProfessor of Neuroscience, University of OxfordDirección de correo verificada de pharm.ox.ac.uk
Stephen ScottProfessor, GSK-CIHR Chair in Neuroscience, Queen's UniversityDirección de correo verificada de queensu.ca
J. Andrew PruszynskiCanada Research Chair in Sensorimotor Neuroscience, Western University, CanadaDirección de correo verificada de uwo.ca
Pontus StrimlingStockholms UniversitetDirección de correo verificada de iffs.se

Timothy P. Lillicrap

Senior Research Scientist, Google DeepMind

Dirección de correo verificada de google.com - Página principal

Machine Learning Deep Learning Neuroscience Reinforcement Learning Memory


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Mastering the game of Go with deep neural networks and tree search D Silver, A Huang, CJ Maddison, A Guez, L Sifre, G Van Den Driessche, ... nature 529 (7587), 484-489, 2016	9601	2016
Continuous control with deep reinforcement learning TP Lillicrap, JJ Hunt, A Pritzel, N Heess, T Erez, Y Tassa, D Silver, ... ICLR 2016; arXiv preprint arXiv:1509.02971, 2015	5244	2015
Mastering the game of go without human knowledge D Silver, J Schrittwieser, K Simonyan, I Antonoglou, A Huang, A Guez, ... nature 550 (7676), 354-359, 2017	5018	2017
Asynchronous methods for deep reinforcement learning V Mnih, AP Badia, M Mirza, A Graves, TP Lillicrap, T Harley, D Silver, ... arXiv:1602.01783, 2016	4527	2016
Matching networks for one shot learning O Vinyals, C Blundell, T Lillicrap, K Kavukcuoglu, D Wierstra arXiv preprint arXiv:1606.04080, 2016	2437	2016
Meta-learning with memory-augmented neural networks A Santoro, S Bartunov, M Botvinick, D Wierstra, T Lillicrap International conference on machine learning, 1842-1850, 2016	1267*	2016
A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play D Silver, T Hubert, J Schrittwieser, I Antonoglou, M Lai, A Guez, M Lanctot, ... Science 362 (6419), 1140-1144, 2018	1198	2018
A simple neural network module for relational reasoning A Santoro, D Raposo, DGT Barrett, M Malinowski, R Pascanu, P Battaglia, ... arXiv preprint arXiv:1706.01427, 2017	943	2017
Mastering chess and shogi by self-play with a general reinforcement learning algorithm D Silver, T Hubert, J Schrittwieser, I Antonoglou, M Lai, A Guez, M Lanctot, ... arXiv preprint arXiv:1712.01815, 2017	923	2017
Deep reinforcement learning for robotic manipulation S Gu, E Holly, T Lillicrap, S Levine arXiv:1610.00633, 2016	870*	2016
Continuous deep Q-learning with model-based acceleration S Gu, T Lillicrap, I Sutskever, S Levine ICML2016; arXiv:1603.00748 [cs.LG], 2016	691	2016
Why copy others? Insights from the social learning strategies tournament L Rendell, R Boyd, D Cownden, M Enquist, K Eriksson, MW Feldman, ... Science 328 (5975), 208-213, 2010	691	2010
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	654	2019
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	470	2017
Random synaptic feedback weights support error backpropagation for deep learning TP Lillicrap, D Cownden, DB Tweed, CJ Akerman Nature communications 7 (1), 1-10, 2016	387	2016
Learning continuous control policies by stochastic value gradients N Heess, G Wayne, D Silver, T Lillicrap, Y Tassa, T Erez arXiv preprint arXiv:1510.09142, 2015	372	2015
Learning latent dynamics for planning from pixels D Hafner, T Lillicrap, I Fischer, R Villegas, D Ha, H Lee, J Davidson International Conference on Machine Learning, 2555-2565, 2019	329	2019
Vector-based navigation using grid-like representations in artificial agents A Banino, C Barry, B Uria, C Blundell, T Lillicrap, P Mirowski, A Pritzel, ... Nature 557 (7705), 429-433, 2018	306	2018
Alphastar: Mastering the real-time strategy game starcraft ii O Vinyals, I Babuschkin, J Chung, M Mathieu, M Jaderberg, ... DeepMind blog 2, 2019	276	2019
Q-prop: Sample-efficient policy gradient with an off-policy critic S Gu, T Lillicrap, Z Ghahramani, RE Turner, S Levine arXiv preprint arXiv:1611.02247, 2016	251	2016

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