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Alchemy: A structured task distribution for meta-reinforcement learning


Feb 04, 2021
Jane X. Wang, Michael King, Nicolas Porcel, Zeb Kurth-Nelson, Tina Zhu, Charlie Deck, Peter Choy, Mary Cassin, Malcolm Reynolds, Francis Song, Gavin Buttimore, David P. Reichert, Neil Rabinowitz, Loic Matthey, Demis Hassabis, Alexander Lerchner, Matthew Botvinick

* 16 pages, 9 figures 

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Meta-learning in natural and artificial intelligence


Nov 26, 2020
Jane X. Wang


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Temporal Difference Uncertainties as a Signal for Exploration


Oct 05, 2020
Sebastian Flennerhag, Jane X. Wang, Pablo Sprechmann, Francesco Visin, Alexandre Galashov, Steven Kapturowski, Diana L. Borsa, Nicolas Heess, Andre Barreto, Razvan Pascanu

* 8 pages, 11 figures, 5 tables 

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Deep Reinforcement Learning and its Neuroscientific Implications


Jul 07, 2020
Matthew Botvinick, Jane X. Wang, Will Dabney, Kevin J. Miller, Zeb Kurth-Nelson

* 22 pages, 5 figures 

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Meta-learning of Sequential Strategies


May 08, 2019
Pedro A. Ortega, Jane X. Wang, Mark Rowland, Tim Genewein, Zeb Kurth-Nelson, Razvan Pascanu, Nicolas Heess, Joel Veness, Alex Pritzel, Pablo Sprechmann, Siddhant M. Jayakumar, Tom McGrath, Kevin Miller, Mohammad Azar, Ian Osband, Neil Rabinowitz, András György, Silvia Chiappa, Simon Osindero, Yee Whye Teh, Hado van Hasselt, Nando de Freitas, Matthew Botvinick, Shane Legg

* DeepMind Technical Report (15 pages, 6 figures) 

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Been There, Done That: Meta-Learning with Episodic Recall


Jul 06, 2018
Samuel Ritter, Jane X. Wang, Zeb Kurth-Nelson, Siddhant M. Jayakumar, Charles Blundell, Razvan Pascanu, Matthew Botvinick

* ICML 2018 

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A high-reproducibility and high-accuracy method for automated topic classification


Feb 03, 2014
Andrea Lancichinetti, M. Irmak Sirer, Jane X. Wang, Daniel Acuna, Konrad Körding, Luís A. Nunes Amaral

* 23 pages, 24 figures 

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