Timothy P. Lillicrap

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David SilverDeepMind, UCLPatvirtintas el. paštas google.com
Adam SantoroGoogle DeepMindPatvirtintas el. paštas google.com
Arthur GuezGoogle DeepMindPatvirtintas el. paštas google.com
Daan WierstraPrincipal Scientist, DeepMindPatvirtintas el. paštas google.com
Yuval TassaSenior Research Scientist, Google DeepMindPatvirtintas el. paštas google.com
Jonathan J HuntTwitterPatvirtintas el. paštas me.net.nz
koray kavukcuogluDeepMindPatvirtintas el. paštas kavukcuoglu.org
Sergey LevineUC Berkeley, Physical IntelligencePatvirtintas el. paštas eecs.berkeley.edu
Tom ErezResearcher, DeepMindPatvirtintas el. paštas google.com
Shixiang Shane GuGoogle DeepMindPatvirtintas el. paštas google.com
Ilya SutskeverCo-Founder and Chief Scientist at Safe Superintelligence IncPatvirtintas el. paštas ssi.inc
Blake RichardsMila + McGill UniversityPatvirtintas el. paštas mila.quebec
Chris J. MaddisonUniversity of TorontoPatvirtintas el. paštas cs.toronto.edu
Alexander PritzelDeepmindPatvirtintas el. paštas google.com
Daniel CowndenResearch Fellow, University of St AndrewsPatvirtintas el. paštas st-andrews.ac.uk
Colin AkermanProfessor of Neuroscience, University of OxfordPatvirtintas el. paštas pharm.ox.ac.uk
Stephen ScottProfessor, Department of Biomedical and Molecular Sciences, Queen's UniversityPatvirtintas el. paštas queensu.ca
Alex GravesUniversity of TorontoPatvirtintas el. paštas cs.toronto.edu
J. Andrew PruszynskiAssociate Professor, Canada Research Chair in Sensorimotor Neuroscience, Western University, CanadaPatvirtintas el. paštas uwo.ca
Pontus StrimlingThe institute for futures studiesPatvirtintas el. paštas iffs.se

Stebėti

Timothy P. Lillicrap

Director of Research, Google DeepMind

Patvirtintas el. paštas google.com - Pagrindinis puslapis

Deep Learning Reinforcement Learning Neuroscience


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
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	20974	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	18388	2015
Asynchronous methods for deep reinforcement learning V Mnih, AP Badia, M Mirza, A Graves, TP Lillicrap, T Harley, D Silver, ... arXiv:1602.01783, 2016	12389	2016
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	11935	2017
Matching networks for one shot learning O Vinyals, C Blundell, T Lillicrap, K Kavukcuoglu, D Wierstra arXiv preprint arXiv:1606.04080, 2016	8968	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	5105	2018
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	5053	2019
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	3245	2016
Mastering atari, go, chess and shogi by planning with a learned model J Schrittwieser, I Antonoglou, T Hubert, K Simonyan, L Sifre, S Schmitt, ... Nature 588 (7839), 604-609, 2020	2705	2020
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	2601	2017
Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ... arXiv preprint arXiv:2312.11805, 2023	2453	2023
Deep reinforcement learning for robotic manipulation S Gu, E Holly, T Lillicrap, S Levine arXiv:1610.00633, 2016	2161*	2016
A simple neural network module for relational reasoning A Santoro, D Raposo, DG Barrett, M Malinowski, R Pascanu, P Battaglia, ... Advances in neural information processing systems 30, 2017	1966	2017
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	1699	2019
Dream to control: Learning behaviors by latent imagination D Hafner, T Lillicrap, J Ba, M Norouzi arXiv preprint arXiv:1912.01603, 2019	1460	2019
Continuous deep Q-learning with model-based acceleration S Gu, T Lillicrap, I Sutskever, S Levine ICML2016; arXiv:1603.00748 [cs.LG], 2016	1351	2016
Experience replay for continual learning D Rolnick, A Ahuja, J Schwarz, T Lillicrap, G Wayne Advances in neural information processing systems 32, 2019	1205	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	1143	2017
A deep learning framework for neuroscience BA Richards, TP Lillicrap, P Beaudoin, Y Bengio, R Bogacz, ... Nature neuroscience 22 (11), 1761-1770, 2019	1076	2019
Backpropagation and the brain TP Lillicrap, A Santoro, L Marris, CJ Akerman, G Hinton Nature Reviews Neuroscience 21 (6), 335-346, 2020	1019	2020

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