Jonathan D. Cohen

Publication Activity (10 Years)

Years Active: 1989-2024
Publications (10 Years): 51

Top Topics

Reinforcement Learning Agents

Automatic Processing

Top Venues

Publications

Declan Campbell, Jonathan D. Cohen
A Relational Inductive Bias for Dimensional Abstraction in Neural Networks. CoRR (2024)
Awni Altabaa, Taylor Whittington Webb, Jonathan D. Cohen, John Lafferty
Abstractors and relational cross-attention: An inductive bias for explicit relational reasoning in Transformers. ICLR (2024)
Shanka Subhra Mondal, Jonathan D. Cohen, Taylor W. Webb
Slot Abstractors: Toward Scalable Abstract Visual Reasoning. CoRR (2024)
Taylor W. Webb, Steven M. Frankland, Awni Altabaa, Kamesh Krishnamurthy, Declan Campbell, Jacob L. Russin, Randall C. O'Reilly, John Lafferty, Jonathan D. Cohen
The Relational Bottleneck as an Inductive Bias for Efficient Abstraction. CoRR (2023)
Shanka Subhra Mondal, Steven Frankland, Taylor Webb, Jonathan D. Cohen
Determinantal Point Process Attention Over Grid Codes Supports Out of Distribution Generalization. CoRR (2023)
Simon N. Segert, Jonathan D. Cohen
Beyond Transformers for Function Learning. CoRR (2023)
Sreejan Kumar, Ishita Dasgupta, Nathaniel D. Daw, Jonathan D. Cohen, Thomas L. Griffiths
Disentangling Abstraction from Statistical Pattern Matching in Human and Machine Learning. PLoS Comput. Biol. 19 (8) (2023)
Taylor W. Webb, Shanka Subhra Mondal, Jonathan D. Cohen
Systematic Visual Reasoning through Object-Centric Relational Abstraction. CoRR (2023)
Taylor Webb, Shanka Subhra Mondal, Jonathan D. Cohen
Systematic Visual Reasoning through Object-Centric Relational Abstraction. NeurIPS (2023)
Raghavendra Pradyumna Pothukuchi, Leon Lufkin, Yu Jun Shen, Alejandro Simon, Rome Thorstenson, Bernardo Eilert Trevisan, Michael Tu, Mudi Yang, Ben Foxman, Viswanatha Srinivas Pothukuchi, Gunnar Epping, Bryant J. Jongkees, Thi Ha Kyaw, Jerome R. Busemeyer, Jonathan D. Cohen, Abhishek Bhattacharjee
Quantum Cognitive Modeling: New Applications and Systems Research Directions. CoRR (2023)
Awni Altabaa, Taylor Webb, Jonathan D. Cohen, John Lafferty
Abstractors: Transformer Modules for Symbolic Message Passing and Relational Reasoning. CoRR (2023)
Ryan Pyle, Sebastian Musslick, Jonathan D. Cohen, Ankit B. Patel
A Quantitative Approach to Predicting Representational Learning and Performance in Neural Networks. CoRR (2023)
Zack Dulberg, Rachit Dubey, Isabel M. Berwian, Jonathan D. Cohen
Modularity benefits reinforcement learning agents with competing homeostatic drives. CoRR (2022)
Sreejan Kumar, Carlos G. Correa, Ishita Dasgupta, Raja Marjieh, Michael Y. Hu, Robert D. Hawkins, Jonathan D. Cohen, Nathaniel D. Daw, Karthik Narasimhan, Tom Griffiths
Using natural language and program abstractions to instill human inductive biases in machines. NeurIPS (2022)
Grant Wallace, Stephen Polcyn, Paula P. Brooks, Anne C. Mennen, Ke Zhao, Paul S. Scotti, Sebastian Michelmann, Kai Li, Nicholas B. Turk-Browne, Jonathan D. Cohen, Kenneth A. Norman
RT-Cloud: A cloud-based software framework to simplify and standardize real-time fMRI. NeuroImage 257 (2022)
Ján Veselý, Raghavendra Pradyumna Pothukuchi, Ketaki Joshi, Samyak Gupta, Jonathan D. Cohen, Abhishek Bhattacharjee
Distill: Domain-Specific Compilation for Cognitive Models. CGO (2022)
Simon N. Segert, Jonathan D. Cohen
A Self-Supervised Framework for Function Learning and Extrapolation. Trans. Mach. Learn. Res. 2022 (2022)
Marius Catalin Iordan, Tyler Giallanza, Cameron T. Ellis, Nicole M. Beckage, Jonathan D. Cohen
Context Matters: Recovering Human Semantic Structure from Machine Learning Analysis of Large-Scale Text Corpora. Cogn. Sci. 46 (2) (2022)
Simon N. Segert, Jonathan D. Cohen
A Self-Supervised Framework for Function Learning and Extrapolation. CoRR (2021)
Ján Veselý, Raghavendra Pradyumna Pothukuchi, Ketaki Joshi, Samyak Gupta, Jonathan D. Cohen, Abhishek Bhattacharjee
Cognac: Domain-Specific Compilation for Cognitive Models. CoRR (2021)
Sreejan Kumar, Ishita Dasgupta, Jonathan D. Cohen, Nathaniel D. Daw, Thomas L. Griffiths
Meta-Learning of Structured Task Distributions in Humans and Machines. ICLR (2021)
Taylor Whittington Webb, Ishan Sinha, Jonathan D. Cohen
Emergent Symbols through Binding in External Memory. ICLR (2021)
Sebastian Musslick, Maria Wirzberger, Ivan Grahek, Laura Bustamante, Amitai Shenhav, Jonathan D. Cohen
Mental effort: One construct, many faces? CogSci (2020)
Mark K. Ho, David Abel, Jonathan D. Cohen, Michael L. Littman, Thomas L. Griffiths
The Efficiency of Human Cognition Reflects Planned Information Processing. CoRR (2020)
Ishan Sinha, Taylor W. Webb, Jonathan D. Cohen
A Memory-Augmented Neural Network Model of Abstract Rule Learning. CoRR (2020)
Zachary Dulberg, Jonathan D. Cohen
Learning Canonical Transformations. CoRR (2020)
Sreejan Kumar, Ishita Dasgupta, Jonathan D. Cohen, Nathaniel D. Daw, Thomas L. Griffiths
Meta-Learning of Compositional Task Distributions in Humans and Machines. CoRR (2020)
Sachin Ravi, Sebastian Musslick, Maia Hamin, Theodore L. Willke, Jonathan D. Cohen
Navigating the Trade-Off between Multi-Task Learning and Learning to Multitask in Deep Neural Networks. CoRR (2020)
Noga Alon, Jonathan D. Cohen, Thomas L. Griffiths, Pasin Manurangsi, Daniel Reichman, Igor Shinkar, Tal Wagner, Alexander Y. Ku
Multitasking Capacity: Hardness Results and Improved Constructions. SIAM J. Discret. Math. 34 (1) (2020)
Taylor W. Webb, Zachary Dulberg, Steven M. Frankland, Alexander A. Petrov, Randall C. O'Reilly, Jonathan D. Cohen
Learning Representations that Support Extrapolation. CoRR (2020)
Mark K. Ho, David Abel, Jonathan D. Cohen, Michael L. Littman, Thomas L. Griffiths
People Do Not Just Plan, They Plan to Plan. AAAI (2020)
Taylor W. Webb, Ishan Sinha, Jonathan D. Cohen
Emergent Symbols through Binding in External Memory. CoRR (2020)
Sebastian Musslick, Jonathan D. Cohen, Amitai Shenhav
Decomposing Individual Differences in Cognitive Control: A Model-Based Approach. CogSci (2019)
Sebastian Musslick, Anastasia S. Bizyaeva, Shamay Agaron, Naomi Ehrich Leonard, Jonathan D. Cohen
Stability-Flexibility Dilemma in Cognitive Control: A Dynamical System Perspective. CogSci (2019)
Sebastian Musslick, Abigail Novick Hoskin, Taylor W. Webb, Steven Frankland, Jonathan D. Cohen, Rebecca L. Jackson, Matthew A. Lambon Ralph, Lang Chen, Timothy T. Rogers, Randall C. O'Reilly, Alexander A. Petrov
Understanding interactions amongst cognitive control, learning and representation. CogSci (2019)
Sebastian Musslick, Jonathan D. Cohen
A Mechanistic Account of Constraints on Control-Dependent Processing: Shared Representation, Conflict and Persistence. CogSci (2019)
Marius Catalin Iordan, Tyler Giallanza, Cameron T. Ellis, Nicole Beckage, Jonathan D. Cohen
Context Matters: Recovering Human Semantic Structure from Machine Learning Analysis of Large-Scale Text Corpora. CoRR (2019)
Markus Spitzer, Sebastian Musslick, Michael Shvartsman, Amitai Shenhav, Jonathan D. Cohen
Asymmetric Switch Costs as a Function of Task Strength. CogSci (2019)
Noga Alon, Jonathan D. Cohen, Thomas L. Griffiths, Pasin Manurangsi, Daniel Reichman, Igor Shinkar, Tal Wagner, Alexander Y. Ku
Multitasking Capacity: Hardness Results and Improved Constructions. CoRR (2018)
Sebastian Musslick, Jonathan D. Cohen, Amitai Shenhav
Estimating the costs of cognitive control from task performance: theoretical validation and potential pitfalls. CogSci (2018)
Yotam Sagiv, Sebastian Musslick, Yael Niv, Jonathan D. Cohen
Efficiency of learning vs. processing: Towards a normative theory of multitasking. CogSci (2018)
Sebastian Musslick, Seong Jun Jang, Michael Shvartsman, Amitai Shenhav, Jonathan D. Cohen
Constraints associated with cognitive control and the stability-flexibility dilemma. CogSci (2018)
Michael Shvartsman, Narayanan Sundaram, Mikio Aoi, Adam Charles, Theodore L. Willke, Jonathan D. Cohen
Matrix-normal models for fMRI analysis. AISTATS (2018)
Kayhan Özcimder, Biswadip Dey, Sebastian Musslick, Giovanni Petri, Nesreen K. Ahmed, Theodore L. Willke, Jonathan D. Cohen
A Formal Approach to Modeling the Cost of Cognitive Control. CogSci (2017)
Vikranth R. Bejjanki, Rava Azeredo da Silveira, Jonathan D. Cohen, Nicholas B. Turk-Browne
Noise correlations in the human brain and their impact on pattern classification. PLoS Comput. Biol. 13 (8) (2017)
Olga Lositsky, Michael Shvartsman, Robert C. Wilson, Jonathan D. Cohen
Adaptive response priors in context-dependent decision-making. CogSci (2017)
Sebastian Musslick, Andrew Saxe, Kayhan Özcimder, Biswadip Dey, Greg Henselman, Jonathan D. Cohen
Multitasking Capability Versus Learning Efficiency in Neural Network Architectures. CogSci (2017)
Noga Alon, Daniel Reichman, Igor Shinkar, Tal Wagner, Sebastian Musslick, Jonathan D. Cohen, Tom Griffiths, Biswadip Dey, Kayhan Özcimder
A graph-theoretic approach to multitasking. NIPS (2017)
Sebastian Musslick, Biswadip Dey, Kayhan Özcimder, Md. Mostofa Ali Patwary, Theodore L. Willke, Jonathan D. Cohen
Controlled vs. Automatic Processing: A Graph-Theoretic Approach to the Analysis of Serial vs. Parallel Processing in Neural Network Architectures. CogSci (2016)
Jonathan D. Cohen, Biswadip Dey, Tom Griffiths, Sebastian Musslick, Kayhan Özcimder, Daniel Reichman, Igor Shinkar, Tal Wagner
A Graph-Theoretic Approach to Multitasking. CoRR (2016)
Yida Wang, Bryn Keller, Mihai Capota, Michael J. Anderson, Narayanan Sundaram, Jonathan D. Cohen, Kai Li, Nicholas B. Turk-Browne, Theodore L. Willke
Real-time full correlation matrix analysis of fMRI data. IEEE BigData (2016)
Yida Wang, Michael J. Anderson, Jonathan D. Cohen, Alexander Heinecke, Kai Li, Nadathur Satish, Narayanan Sundaram, Nicholas B. Turk-Browne, Theodore L. Willke
Full correlation matrix analysis of fMRI data on Intel® Xeon Phi™ coprocessors. SC (2015)
Michael Shvartsman, Vaibhav Srivastava, Jonathan D. Cohen
A Theory of Decision Making Under Dynamic Context. NIPS (2015)
Matthew Botvinick, Jonathan D. Cohen
The Computational and Neural Basis of Cognitive Control: Charted Territory and New Frontiers. Cogn. Sci. 38 (6) (2014)
Philip Holmes, Jonathan D. Cohen
Optimality and Some of Its Discontents: Successes and Shortcomings of Existing Models for Binary Decisions. Top. Cogn. Sci. 6 (2) (2014)
Jeremy R. Manning, Rajesh Ranganath, Waitsang Keung, Nicholas B. Turk-Browne, Jonathan D. Cohen, Kenneth A. Norman, David M. Blei
Hierarchical topographic factor analysis. PRNI (2014)
Michael T. Todd, Leigh E. Nystrom, Jonathan D. Cohen
Confounds in multivariate pattern analysis: Theory and rule representation case study. NeuroImage 77 (2013)
Andrea Nedic, Damon Tomlin, Philip Holmes, Deborah A. Prentice, Jonathan D. Cohen
A Decision Task in a Social Context: Human Experiments, Models, and Analyses of Behavioral Data. Proc. IEEE 100 (3) (2012)
Sarah E. Forster, Cameron S. Carter, Jonathan D. Cohen, Raymond Y. Cho
Parametric Manipulation of the Conflict Signal and Control-state Adaptation. J. Cogn. Neurosci. 23 (4) (2011)
Nick Yeung, Jonathan D. Cohen, Matthew Botvinick
Errors of interpretation and modeling: A reply to Grinband et al. NeuroImage 57 (2) (2011)
Juan Gao, KongFatt Wong-Lin, Philip Holmes, Patrick Simen, Jonathan D. Cohen
Sequential Effects in Two-Choice Reaction Time Tasks: Decomposition and Synthesis of Mechanisms. Neural Comput. 21 (9) (2009)
Eric Shea-Brown, Mark S. Gilzenrat, Jonathan D. Cohen
Optimization of Decision Making in Multilayer Networks: The Role of Locus Coeruleus. Neural Comput. 20 (12) (2008)
Andrea Nedic, Damon Tomlin, Philip Holmes, Deborah A. Prentice, Jonathan D. Cohen
A simple decision task in a social context: Experiments, a model, and preliminary analyses of behavioral data. CDC (2008)
Yuan Sophie Liu, Philip Holmes, Jonathan D. Cohen
A Neural Network Model of the Eriksen Task: Reduction, Analysis, and Data Fitting. Neural Comput. 20 (2) (2008)
Angela J. Yu, Jonathan D. Cohen
Sequential effects: Superstition or rational behavior? NIPS (2008)
Michael T. Todd, Yael Niv, Jonathan D. Cohen
Learning to Use Working Memory in Partially Observable Environments through Dopaminergic Reinforcement. NIPS (2008)
Patrick Simen, Jonathan D. Cohen, Philip Holmes
Rapid decision threshold modulation by reward rate in a neural network. Neural Networks 19 (8) (2006)
Eric Brown, Juan Gao, Philip Holmes, Rafal Bogacz, Mark S. Gilzenrat, Jonathan D. Cohen
Simple Neural Networks that Optimize Decisions. Int. J. Bifurc. Chaos 15 (3) (2005)
Samuel McClure, Mark S. Gilzenrat, Jonathan D. Cohen
An exploration-exploitation model based on norepinepherine and dopamine activity. NIPS (2005)
Philip Holmes, Eric Shea-Brown, Jeff Moehlis, Rafal Bogacz, Juan Gao, Gary Aston-Jones, Ed Clayton, Janusz Rajkowski, Jonathan D. Cohen
Optimal Decisions: From Neural Spikes, through Stochastic Differential Equations, to Behavior. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. (10) (2005)
James K. Rilling, Alan G. Sanfey, Jessica A. Aronson, Leigh E. Nystrom, Jonathan D. Cohen
The neural correlates of theory of mind within interpersonal interactions. NeuroImage 22 (4) (2004)
Kate Fissell, Eugene Tseytlin, Daniel Cunningha, Karthickeyan Iyer, Cameron S. Carter, Walter Schneider, Jonathan D. Cohen
Fiswidgets - A graphical computing environment for neuroimaging analysis. Neuroinformatics 1 (1) (2003)
P. Read Montague, Gregory S. Berns, Jonathan D. Cohen, Samuel M. McClure, Giuseppe Pagnoni, Mukesh Dhamala, Michael C. Wiest, Igor Karpov, Richard D. King, Nathan Apple, Ronald E. Fisher
Hyperscanning: Simultaneous fMRI during Linked Social Interactions. NeuroImage 16 (4) (2002)
Mark S. Gilzenrat, Benjamin D. Holmes, Janusz Rajkowski, Gary Aston-Jones, Jonathan D. Cohen
Simplified dynamics in a model of noradrenergic modulation of cognitive performance. Neural Networks 15 (4-6) (2002)
Vincent van Veen, Jonathan D. Cohen, Matthew M. Botvinick, V. Andrew Stenger, Cameron S. Carter
Anterior Cingulate Cortex, Conflict Monitoring, and Levels of Processing. NeuroImage 14 (6) (2001)
Todd S. Braver, Jonathan D. Cohen, David Servan-Schreiber
A Computational Model of Prefrontal Cortex Function. NIPS (1994)
David Servan-Schreiber, Harry Printz, Jonathan D. Cohen
The Effect of Catecholamines on Performance: From Unit to System Behavior. NIPS (1989)