Jane X. Wang - RankMe

37 papers A* 7A 1B 1Journal 28

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Exploring exploration with foundation agents in interactive environments. Trans. Mach. Learn. Res. Daniel P. Sawyer, Nan Rosemary Ke, Hubert Soyer, Martin Engelcke, John Reid, David P. Reichert, Drew A. Hudson, Alexander Lerchner, Danilo Jimenez Rezende, Timothy P. Lillicrap, Michael Curtis Mozer, Jane X. Wang
2024	J	`jnl`	A social path to human-like artificial intelligence. CoRR Edgar A. Duéñez-Guzmán, Suzanne Sadedin, Jane X. Wang, Kevin R. McKee, Joel Z. Leibo
2024	J	`jnl`	Can foundation models actively gather information in interactive environments to test hypotheses? CoRR Nan Rosemary Ke, Danny P. Sawyer, Hubert Soyer, Martin Engelcke, David P. Reichert, Drew A. Hudson, John Reid, Alexander Lerchner, Danilo Jimenez Rezende, Timothy P. Lillicrap, Michael Mozer, Jane X. Wang
2024	A*	`conf`	CogBench: a large language model walks into a psychology lab. ICML Julian Coda-Forno, Marcel Binz, Jane X. Wang, Eric Schulz
2024	J	`jnl`	CogBench: a large language model walks into a psychology lab. CoRR Julian Coda-Forno, Marcel Binz, Jane X. Wang, Eric Schulz
2024	J	`jnl`	Scaling Instructable Agents Across Many Simulated Worlds. CoRR SIMA Team, Maria Abi Raad, Arun Ahuja, Catarina Barros, Frederic Besse, Andrew Bolt, Adrian Bolton, Bethanie Brownfield, Gavin Buttimore, Max Cant, Sarah Chakera, Stephanie C. Y. Chan, Jeff Clune, Adrian Collister, Vikki Copeman, Alex Cullum, Ishita Dasgupta, Dario de Cesare, Julia Di Trapani, Yani Donchev, Emma Dunleavy, Martin Engelcke, Ryan Faulkner, Frankie Garcia, Charles Gbadamosi, Zhitao Gong, Lucy Gonzalez, Kshitij Gupta, Karol Gregor, Arne Olav Hallingstad, Tim Harley, Sam Haves, Felix Hill, Ed Hirst, Drew A. Hudson, Jony Hudson, Steph Hughes-Fitt, Danilo J. Rezende, Mimi Jasarevic, Laura Kampis, Nan Rosemary Ke, Thomas Keck, Junkyung Kim, Oscar Knagg, Kavya Kopparapu, Andrew K. Lampinen, Shane Legg, Alexander Lerchner, Marjorie Limont, Yulan Liu, Maria Loks-Thompson, Joseph Marino, Kathryn Martin Cussons, Loic Matthey, Siobhan Mcloughlin, Piermaria Mendolicchio, Hamza Merzic, Anna Mitenkova, Alexandre Moufarek, Valéria Oliveira, Yanko Gitahy Oliveira, Hannah Openshaw, Renke Pan, Aneesh Pappu, Alex Platonov, Ollie Purkiss, David P. Reichert, John Reid, Pierre Harvey Richemond, Tyson Roberts, Giles Ruscoe, Jaume Sanchez Elias, Tasha Sandars, Daniel P. Sawyer, Tim Scholtes, Guy Simmons, Daniel Slater, Hubert Soyer, Heiko Strathmann, Peter Stys, Allison C. Tam, Denis Teplyashin, Tayfun Terzi, Davide Vercelli, Bojan Vujatovic, Marcus Wainwright, Jane X. Wang, Zhengdong Wang, Daan Wierstra, Duncan Williams, Nathaniel Wong, Sarah York, Nick Young
2023	J	`jnl`	A social path to human-like artificial intelligence. Nat. Mac. Intell. Edgar A. Duéñez-Guzmán, Suzanne Sadedin, Jane X. Wang, Kevin R. McKee, Joel Z. Leibo
2023	J	`jnl`	DiscoGen: Learning to Discover Gene Regulatory Networks. CoRR 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
2023	A*	`conf`	Learning to Induce Causal Structure. ICLR Nan Rosemary Ke, Silvia Chiappa, Jane X. Wang, Jörg Bornschein, Anirudh Goyal, Mélanie Rey, Theophane Weber, Matthew M. Botvinick, Michael Curtis Mozer, Danilo Jimenez Rezende
2023	J	`jnl`	Meta-Learned Models of Cognition. CoRR Marcel Binz, Ishita Dasgupta, Akshay K. Jagadish, Matthew M. Botvinick, Jane X. Wang, Eric Schulz
2023	A*	`conf`	Meta-in-context learning in large language models. NeurIPS Julian Coda-Forno, Marcel Binz, Zeynep Akata, Matt M. Botvinick, Jane X. Wang, Eric Schulz
2023	J	`jnl`	Meta-in-context learning in large language models. CoRR Julian Coda-Forno, Marcel Binz, Zeynep Akata, Matthew M. Botvinick, Jane X. Wang, Eric Schulz
2023	A*	`conf`	Passive learning of active causal strategies in agents and language models. NeurIPS Andrew K. Lampinen, Stephanie C. Y. Chan, Ishita Dasgupta, Andrew J. Nam, Jane X. Wang
2023	J	`jnl`	Passive learning of active causal strategies in agents and language models. CoRR Andrew Kyle Lampinen, Stephanie C. Y. Chan, Ishita Dasgupta, Andrew J. Nam, Jane X. Wang
2022	J	`jnl`	Beyond Bayes-optimality: meta-learning what you know you don't know. CoRR 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
2022	J	`jnl`	Can language models learn from explanations in context? CoRR 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
2022	A*	`conf`	Data Distributional Properties Drive Emergent In-Context Learning in Transformers. NeurIPS Stephanie C. Y. Chan, Adam Santoro, Andrew K. Lampinen, Jane X. Wang, Aaditya K. Singh, Pierre H. Richemond, James L. McClelland, Felix Hill
2022	J	`jnl`	Data Distributional Properties Drive Emergent In-Context Learning in Transformers. CoRR Stephanie C. Y. Chan, Adam Santoro, Andrew K. Lampinen, Jane X. Wang, Aaditya K. Singh, Pierre H. Richemond, Jay McClelland, Felix Hill
2022	J	`jnl`	Semantic Exploration from Language Abstractions and Pretrained Representations. CoRR 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
2022	A*	`conf`	Tell me why! Explanations support learning relational and causal structure. ICML 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
2021	J	`jnl`	Alchemy: A structured task distribution for meta-reinforcement learning. CoRR 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
2021	J	`jnl`	Tell me why! - Explanations support learning of relational and causal structure. CoRR 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
2020	J	`jnl`	Amortized learning of neural causal representations. CoRR Nan Rosemary Ke, Jane X. Wang, Jovana Mitrovic, Martin Szummer, Danilo J. Rezende
2020	J	`jnl`	Deep Reinforcement Learning and its Neuroscientific Implications. CoRR Matthew M. Botvinick, Jane X. Wang, Will Dabney, Kevin J. Miller, Zeb Kurth-Nelson
2020	J	`jnl`	Meta-learning in natural and artificial intelligence. CoRR Jane X. Wang
2020	J	`jnl`	Temporal Difference Uncertainties as a Signal for Exploration. CoRR Sebastian Flennerhag, Jane X. Wang, Pablo Sprechmann, Francesco Visin, Alexandre Galashov, Steven Kapturowski, Diana L. Borsa, Nicolas Heess, André Barreto, Razvan Pascanu
2019	J	`jnl`	Causal Reasoning from Meta-reinforcement Learning. CoRR 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
2019	A	`conf`	Evolving Intrinsic Motivations for Altruistic Behavior. AAMAS Jane X. Wang, Edward Hughes, Chrisantha Fernando, Wojciech M. Czarnecki, Edgar A. Duéñez-Guzmán, Joel Z. Leibo
2019	J	`jnl`	Meta-learning of Sequential Strategies. CoRR 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
2019	J	`jnl`	Structural and Functional MRI Evidence for Distinct Medial Temporal and Prefrontal Roles in Context-dependent Relational Memory. J. Cogn. Neurosci. 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
2018	A*	`conf`	Been There, Done That: Meta-Learning with Episodic Recall. ICML Samuel Ritter, Jane X. Wang, Zeb Kurth-Nelson, Siddhant M. Jayakumar, Charles Blundell, Razvan Pascanu, Matthew M. Botvinick
2018	J	`jnl`	Been There, Done That: Meta-Learning with Episodic Recall. CoRR Samuel Ritter, Jane X. Wang, Zeb Kurth-Nelson, Siddhant M. Jayakumar, Charles Blundell, Razvan Pascanu, Matthew M. Botvinick
2018	B	`conf`	Episodic Control through Meta-Reinforcement Learning. CogSci Samuel Ritter, Jane X. Wang, Zeb Kurth-Nelson, Matthew M. Botvinick
2018	J	`jnl`	Evolving intrinsic motivations for altruistic behavior. CoRR Jane X. Wang, Edward Hughes, Chrisantha Fernando, Wojciech M. Czarnecki, Edgar A. Duéñez-Guzmán, Joel Z. Leibo
2016	J	`jnl`	Learning to reinforcement learn. CoRR Jane X. Wang, Zeb Kurth-Nelson, Dhruva Tirumala, Hubert Soyer, Joel Z. Leibo, Rémi Munos, Charles Blundell, Dharshan Kumaran, Matthew M. Botvinick
2014	J	`jnl`	A high-reproducibility and high-accuracy method for automated topic classification. CoRR Andrea Lancichinetti, M. Irmak Sirer, Jane X. Wang, Daniel E. Acuna, Konrad P. Körding, Luís A. Nunes Amaral
2012	J	`jnl`	Interactions of Excitatory and Inhibitory Feedback Topologies in Facilitating Pattern Separation and Retrieval. Neural Comput. Jane X. Wang, Michal Zochowski