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ORCIDJane X. Wang
Person information
- affiliation: Google DeepMind, London, UK
- affiliation: Northwestern University, Feinberg School of Medicine, Chicago, IL, USA
- affiliation (PhD 2010): University of Michigan, Ann Arbor, MI, USA
Other persons with the same name
- Jane Wang — disambiguation page
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2020 – today
- 2023
[i22]Nan Rosemary Ke, Sara-Jane Dunn, Jörg Bornschein, Silvia Chiappa, Mélanie Rey, Jean-Baptiste Lespiau, Albin Cassirer, Jane X. Wang, Theophane Weber, David G. T. Barrett, Matthew M. Botvinick, Anirudh Goyal, Michael Mozer, Danilo J. Rezende:
DiscoGen: Learning to Discover Gene Regulatory Networks. CoRR abs/2304.05823 (2023)- [i21]Marcel Binz, Ishita Dasgupta, Akshay Jagadish, Matthew M. Botvinick, Jane X. Wang, Eric Schulz:
Meta-Learned Models of Cognition. CoRR abs/2304.06729 (2023) - [i20]Julian Coda-Forno, Marcel Binz, Zeynep Akata, Matthew M. Botvinick, Jane X. Wang, Eric Schulz:
Meta-in-context learning in large language models. CoRR abs/2305.12907 (2023) - 2022
- [c10]Andrew K. Lampinen, Ishita Dasgupta, Stephanie C. Y. Chan, Kory W. Mathewson, Mh Tessler, Antonia Creswell, James L. McClelland, Jane Wang, Felix Hill:
Can language models learn from explanations in context? EMNLP (Findings) 2022: 537-563 - [c9]Andrew K. Lampinen, Nicholas A. Roy, Ishita Dasgupta, Stephanie C. Y. Chan, Allison C. Tam, James L. McClelland, Chen Yan, Adam Santoro, Neil C. Rabinowitz, Jane X. Wang, Felix Hill:
Tell me why! Explanations support learning relational and causal structure. ICML 2022: 11868-11890 - [c8]Allison C. Tam, Neil C. Rabinowitz, Andrew K. Lampinen, Nicholas A. Roy, Stephanie C. Y. Chan, DJ Strouse, Jane Wang, Andrea Banino, Felix Hill:
Semantic Exploration from Language Abstractions and Pretrained Representations. NeurIPS 2022 - [i19]Andrew K. Lampinen, Ishita Dasgupta, Stephanie C. Y. Chan, Kory W. Mathewson, Michael Henry Tessler, Antonia Creswell, James L. McClelland, Jane X. Wang, Felix Hill:
Can language models learn from explanations in context? CoRR abs/2204.02329 (2022) - [i18]Nan Rosemary Ke, Silvia Chiappa, Jane Wang, Jörg Bornschein, Theophane Weber, Anirudh Goyal, Matthew M. Botvinick, Michael Mozer, Danilo Jimenez Rezende:
Learning to Induce Causal Structure. CoRR abs/2204.04875 (2022) - [i17]Allison C. Tam, Neil C. Rabinowitz, Andrew K. Lampinen, Nicholas A. Roy, Stephanie C. Y. Chan, DJ Strouse, Jane X. Wang, Andrea Banino, Felix Hill:
Semantic Exploration from Language Abstractions and Pretrained Representations. CoRR abs/2204.05080 (2022) - [i16]Stephanie C. Y. Chan, Adam Santoro, Andrew K. Lampinen, Jane X. Wang, Aaditya K. Singh, Pierre H. Richemond, Jay McClelland, Felix Hill:
Data Distributional Properties Drive Emergent In-Context Learning in Transformers. CoRR abs/2205.05055 (2022) - [i15]Jordi Grau-Moya, Grégoire Delétang, Markus Kunesch, Tim Genewein, Elliot Catt, Kevin Li, Anian Ruoss, Chris Cundy, Joel Veness, Jane X. Wang, Marcus Hutter, Christopher Summerfield, Shane Legg, Pedro A. Ortega:
Beyond Bayes-optimality: meta-learning what you know you don't know. CoRR abs/2209.15618 (2022) - 2021
- [c7]Jane Wang, Michael King, Nicolas Porcel, Zeb Kurth-Nelson, Tina Zhu, Charles Deck, Peter Choy, Mary Cassin, Malcolm Reynolds, H. Francis Song, Gavin Buttimore, David P. Reichert, Neil C. Rabinowitz, Loic Matthey, Demis Hassabis, Alexander Lerchner, Matt M. Botvinick:
Alchemy: A benchmark and analysis toolkit for meta-reinforcement learning agents. NeurIPS Datasets and Benchmarks 2021 - [i14]Jane X. Wang, Michael King, Nicolas Porcel, Zeb Kurth-Nelson, Tina Zhu, Charlie Deck, Peter Choy, Mary Cassin, Malcolm Reynolds, H. Francis Song, Gavin Buttimore, David P. Reichert, Neil C. Rabinowitz, Loic Matthey, Demis Hassabis, Alexander Lerchner, Matthew M. Botvinick:
Alchemy: A structured task distribution for meta-reinforcement learning. CoRR abs/2102.02926 (2021) - [i13]Andrew K. Lampinen, Nicholas A. Roy, Ishita Dasgupta, Stephanie C. Y. Chan, Allison C. Tam, James L. McClelland, Chen Yan, Adam Santoro, Neil C. Rabinowitz, Jane X. Wang, Felix Hill:
Tell me why! - Explanations support learning of relational and causal structure. CoRR abs/2112.03753 (2021) - 2020
- [i12]Danilo J. Rezende, Ivo Danihelka, George Papamakarios, Nan Rosemary Ke, Ray Jiang, Theophane Weber, Karol Gregor, Hamza Merzic, Fabio Viola, Jane Wang, Jovana Mitrovic, Frederic Besse, Ioannis Antonoglou, Lars Buesing:
Causally Correct Partial Models for Reinforcement Learning. CoRR abs/2002.02836 (2020) - [i11]Matthew M. Botvinick, Jane X. Wang, Will Dabney, Kevin J. Miller, Zeb Kurth-Nelson:
Deep Reinforcement Learning and its Neuroscientific Implications. CoRR abs/2007.03750 (2020) - [i10]Nan Rosemary Ke, Jane X. Wang, Jovana Mitrovic, Martin Szummer, Danilo J. Rezende:
Amortized learning of neural causal representations. CoRR abs/2008.09301 (2020) - [i9]Sebastian Flennerhag, Jane X. Wang, Pablo Sprechmann, Francesco Visin, Alexandre Galashov, Steven Kapturowski, Diana L. Borsa, Nicolas Heess, André Barreto, Razvan Pascanu:
Temporal Difference Uncertainties as a Signal for Exploration. CoRR abs/2010.02255 (2020) - [i8]Jane X. Wang:
Meta-learning in natural and artificial intelligence. CoRR abs/2011.13464 (2020)
2010 – 2019
- 2019
- [j2]Hillary D. Schwarb, Curtis L. Johnson, Michael R. Dulas, Matthew D. J. McGarry, Joseph L. Holtrop, Patrick D. Watson, Jane X. Wang, Joel L. Voss
, Bradley P. Sutton, Neal J. Cohen:
Structural and Functional MRI Evidence for Distinct Medial Temporal and Prefrontal Roles in Context-dependent Relational Memory. J. Cogn. Neurosci. 31(12): 1857-1872 (2019) - [c6]Jane X. Wang, Edward Hughes, Chrisantha Fernando, Wojciech M. Czarnecki, Edgar A. Duéñez-Guzmán, Joel Z. Leibo:
Evolving Intrinsic Motivations for Altruistic Behavior. AAMAS 2019: 683-692 - [i7]Ishita Dasgupta, Jane X. Wang, Silvia Chiappa, Jovana Mitrovic, Pedro A. Ortega, David Raposo, Edward Hughes, Peter W. Battaglia, Matthew M. Botvinick, Zeb Kurth-Nelson:
Causal Reasoning from Meta-reinforcement Learning. CoRR abs/1901.08162 (2019) - [i6]Pedro A. Ortega, Jane X. Wang, Mark Rowland, Tim Genewein, Zeb Kurth-Nelson, Razvan Pascanu, Nicolas Heess, Joel Veness, Alexander Pritzel, Pablo Sprechmann, Siddhant M. Jayakumar, Tom McGrath, Kevin J. Miller, Mohammad Gheshlaghi Azar, Ian Osband, Neil C. Rabinowitz, András György, Silvia Chiappa, Simon Osindero, Yee Whye Teh, Hado van Hasselt, Nando de Freitas, Matthew M. Botvinick, Shane Legg:
Meta-learning of Sequential Strategies. CoRR abs/1905.03030 (2019) - 2018
- [c5]Samuel Ritter, Jane X. Wang, Zeb Kurth-Nelson, Matthew M. Botvinick:
Episodic Control through Meta-Reinforcement Learning. CogSci 2018 - [c4]Chrisantha Fernando, Jakub Sygnowski, Simon Osindero, Jane Wang, Tom Schaul, Denis Teplyashin, Pablo Sprechmann, Alexander Pritzel, Andrei A. Rusu:
Meta-learning by the baldwin effect. GECCO (Companion) 2018: 109-110 - [c3]Chrisantha Fernando, Jakub Sygnowski, Simon Osindero, Jane Wang, Tom Schaul, Denis Teplyashin, Pablo Sprechmann, Alexander Pritzel, Andrei A. Rusu:
Meta-learning by the Baldwin effect. GECCO (Companion) 2018: 1313-1320 - [c2]Samuel Ritter, Jane X. Wang, Zeb Kurth-Nelson, Siddhant M. Jayakumar, Charles Blundell, Razvan Pascanu, Matthew M. Botvinick:
Been There, Done That: Meta-Learning with Episodic Recall. ICML 2018: 4351-4360 - [i5]Samuel Ritter, Jane X. Wang, Zeb Kurth-Nelson, Siddhant M. Jayakumar, Charles Blundell, Razvan Pascanu, Matthew M. Botvinick:
Been There, Done That: Meta-Learning with Episodic Recall. CoRR abs/1805.09692 (2018) - [i4]Chrisantha Thomas Fernando, Jakub Sygnowski, Simon Osindero, Jane Wang, Tom Schaul, Denis Teplyashin, Pablo Sprechmann, Alexander Pritzel, Andrei A. Rusu:
Meta-Learning by the Baldwin Effect. CoRR abs/1806.07917 (2018) - [i3]Jane X. Wang, Edward Hughes, Chrisantha Fernando, Wojciech M. Czarnecki, Edgar A. Duéñez-Guzmán, Joel Z. Leibo:
Evolving intrinsic motivations for altruistic behavior. CoRR abs/1811.05931 (2018) - 2017
- [c1]Jane Wang, Zeb Kurth-Nelson, Hubert Soyer, Joel Z. Leibo, Dhruva Tirumala, Rémi Munos, Charles Blundell, Dharshan Kumaran, Matt M. Botvinick:
Learning to reinforcement learn. CogSci 2017 - 2016
- [i2]Jane X. Wang, Zeb Kurth-Nelson, Dhruva Tirumala, Hubert Soyer, Joel Z. Leibo, Rémi Munos, Charles Blundell, Dharshan Kumaran, Matthew M. Botvinick:
Learning to reinforcement learn. CoRR abs/1611.05763 (2016) - 2014
- [i1]Andrea Lancichinetti, M. Irmak Sirer, Jane X. Wang, Daniel E. Acuna, Konrad P. Körding, Luís A. Nunes Amaral:
A high-reproducibility and high-accuracy method for automated topic classification. CoRR abs/1402.0422 (2014) - 2012
- [j1]Jane X. Wang, Michal Zochowski:
Interactions of Excitatory and Inhibitory Feedback Topologies in Facilitating Pattern Separation and Retrieval. Neural Comput. 24(1): 32-59 (2012)
Coauthor Index
aka: Matthew M. Botvinick
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