Jane X. Wang

发表

Alchemy: A structured task distribution for meta-reinforcement learning pdf

Zeb Kurth-Nelson, Demis Hassabis, Matthew Botvinick, 2021, ArXiv.

Alchemy: A benchmark and analysis toolkit for meta-reinforcement learning agents

Zeb Kurth-Nelson, Demis Hassabis, Matthew Botvinick, 2021, NeurIPS Datasets and Benchmarks.

Prefrontal cortex as a meta-reinforcement learning system

Joel Z. Leibo, Jane X. Wang, D. Hassabis, 2018, bioRxiv.

Learning to reinforcement learn pdf

Zeb Kurth-Nelson, Joel Z. Leibo, Charles Blundell, 2016, CogSci.

Meta-learning of Sequential Strategies pdf

Yee Whye Teh, Razvan Pascanu, Nando de Freitas, 2019, ArXiv.

Meta-learning by the Baldwin effect

Tom Schaul, Simon Osindero, Chrisantha Fernando, 2018, GECCO.

Deep Reinforcement Learning and Its Neuroscientific Implications

Zeb Kurth-Nelson, Kevin J. Miller, Matthew Botvinick, 2020, Neuron.

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

Zeb Kurth-Nelson, Razvan Pascanu, Charles Blundell, 2018, ICML.

Causal Reasoning from Meta-reinforcement Learning pdf

Zeb Kurth-Nelson, Silvia Chiappa, Matthew Botvinick, 2019, ArXiv.

Reinforcement Learning, Fast and Slow

Jane X. Wang, D. Hassabis, C. Blundell, 2019, Trends in Cognitive Sciences.

Meta-reinforcement learning of causal strategies

Pedro A. Ortega, Jane X. Wang, M. Botvinick, 2019 .

Temporal Difference Uncertainties as a Signal for Exploration pdf

Razvan Pascanu, Nicolas Heess, Alexandre Galashov, 2020, ArXiv.

Tell me why! - Explanations support learning of relational and causal structure pdf

Andrew K. Lampinen, James L. McClelland, Felix Hill, 2021, ArXiv.

Data Distributional Properties Drive Emergent In-Context Learning in Transformers

Andrew Kyle Lampinen, Pierre H. Richemond, Stephanie C. Y. Chan, 2022, ArXiv.

Tell me why! Explanations support learning relational and causal structure

James L. McClelland, Andrew Kyle Lampinen, Nicholas A. Roy, 2021, ICML.

Data Distributional Properties Drive Emergent In-Context Learning in Transformers

Andrew Kyle Lampinen, Pierre H. Richemond, Stephanie C. Y. Chan, 2022, ArXiv.

Semantic Exploration from Language Abstractions and Pretrained Representations

Andrew Kyle Lampinen, Nicholas A. Roy, Neil C. Rabinowitz, 2022, ArXiv.

Learning to Induce Causal Structure

Danilo Jimenez Rezende, Nan Rosemary Ke, Jane X. Wang, 2022, ICLR.

Data Distributional Properties Drive Emergent In-Context Learning in Transformers

Andrew Kyle Lampinen, Pierre H. Richemond, Stephanie C. Y. Chan, 2022, ArXiv.

Can language models learn from explanations in context?

James L. McClelland, Andrew Kyle Lampinen, Michael Henry Tessler, 2022, EMNLP.

Beyond Bayes-optimality: meta-learning what you know you don't know

Pedro A. Ortega, Jane X. Wang, J. Veness, 2022, ArXiv.

Episodic Control through Meta-Reinforcement Learning

Zeb Kurth-Nelson, Samuel Ritter, Matthew Botvinick, 2018, CogSci.

Data Distributional Properties Drive Emergent In-Context Learning in Transformers

Andrew Kyle Lampinen, Pierre H. Richemond, Stephanie C. Y. Chan, 2022, NeurIPS.

Evolving intrinsic motivations for altruistic behavior pdf

Joel Z. Leibo, Wojciech Czarnecki, Chrisantha Fernando, 2018, AAMAS.

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

Konrad P. Körding, Luis A. Nunes Amaral, Andrea Lancichinetti, 2014, ArXiv.

Meta-learning in natural and artificial intelligence

Jane X. Wang, Jane X. Wang, 2020, Current Opinion in Behavioral Sciences.

Deep Reinforcement Learning and Its Neuroscientiﬁc Implications

Kevin J. Miller, Will Dabney, Matthew Botvinick, 2020 .

Semantic Exploration from Language Abstractions and Pretrained Representations

Andrew Kyle Lampinen, Nicholas A. Roy, Neil C. Rabinowitz, 2022, NeurIPS.

Temporal Difference Uncertainties as a Signal for Exploration

Jane X. Wang, N. Heess, André Barreto, 2020, ArXiv.

Meta-Learned Models of Cognition

Jane X. Wang, M. Botvinick, Eric Schulz, 2023, ArXiv.

Meta-in-context learning in large language models

Matthew Botvinick, Jane X. Wang, Jane X. Wang, 2023, ArXiv.

Meta-learning by the Baldwin effect

Tom Schaul, Simon Osindero, Chrisantha Fernando, 2018, GECCO.

Causally Correct Partial Models for Reinforcement Learning pdf

Fabio Viola, Karol Gregor, Lars Buesing, 2020, ArXiv.

Passive learning of active causal strategies in agents and language models

Andrew Kyle Lampinen, Stephanie C. Y. Chan, Jane X. Wang, 2023, ArXiv.

DiscoGen: Learning to Discover Gene Regulatory Networks

Danilo Jimenez Rezende, Nan Rosemary Ke, Jane X. Wang, 2023, bioRxiv.

Prefrontal cortex as a meta-reinforcement learning system

Joel Z. Leibo, Jane X. Wang, D. Hassabis, 2018, Nature Neuroscience.

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

Siddhant M. Jayakumar, Jane X. Wang, C. Blundell, 2018, ICML.