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Cognition
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September 4, 2020
Parallelograms revisited: Exploring the limitations of vector space models for simple analogies
Joshua C Peterson, Dawn Chen, Thomas L Griffiths
Cognitive Science
|
January 8, 2023
Extracting Low-Dimensional Psychological Representations from Convolutional Neural Networks
Aditi Jha, Joshua C Peterson, Thomas L Griffiths
Proceedings of the National Academy of Sciences of the United States of America
|
April 4, 2020
Scaling up psychology via Scientific Regret Minimization
Mayank Agrawal, Joshua C Peterson, Thomas L Griffiths
Nature Communications
|
October 28, 2020
Capturing human categorization of natural images by combining deep networks and cognitive models
Ruairidh M Battleday, Joshua C Peterson, Thomas L Griffiths
Annals of the New York Academy of Sciences
|
March 23, 2021
From convolutional neural networks to models of higher-level cognition (and back again)
Ruairidh M Battleday, Joshua C Peterson, Thomas L Griffiths
Cognitive Science
|
September 5, 2018
Evaluating (and Improving) the Correspondence Between Deep Neural Networks and Human Representations
Joshua C Peterson, Joshua T Abbott, Thomas L Griffiths
Journal of Experimental Psychology. General
|
February 22, 2024
The universal law of generalization holds for naturalistic stimuli
Raja Marjieh, Nori Jacoby, Joshua C Peterson, et al.
Nature Human Behaviour
|
June 25, 2025
Capturing the complexity of human strategic decision-making with machine learning
Jian-Qiao Zhu, Joshua C Peterson, Benjamin Enke, et al.
Journal of Experimental Psychology. General
|
April 20, 2023
Stress, intertemporal choice, and mitigation behavior during the COVID-19 pandemic
Mayank Agrawal, Joshua C Peterson, Jonathan D Cohen, et al.
Science (New York, N.Y.)
|
June 11, 2021
Using large-scale experiments and machine learning to discover theories of human decision-making
Joshua C Peterson, David D Bourgin, Mayank Agrawal, et al.
Page
of 2
Search research articles
Search
Showing results (1-10 of 17) with videos related to
Sort By:
Page
of 2
Cognition
|
September 4, 2020
Parallelograms revisited: Exploring the limitations of vector space models for simple analogies
Joshua C Peterson, Dawn Chen, Thomas L Griffiths
Cognitive Science
|
January 8, 2023
Extracting Low-Dimensional Psychological Representations from Convolutional Neural Networks
Aditi Jha, Joshua C Peterson, Thomas L Griffiths
Proceedings of the National Academy of Sciences of the United States of America
|
April 4, 2020
Scaling up psychology via Scientific Regret Minimization
Mayank Agrawal, Joshua C Peterson, Thomas L Griffiths
Nature Communications
|
October 28, 2020
Capturing human categorization of natural images by combining deep networks and cognitive models
Ruairidh M Battleday, Joshua C Peterson, Thomas L Griffiths
Annals of the New York Academy of Sciences
|
March 23, 2021
From convolutional neural networks to models of higher-level cognition (and back again)
Ruairidh M Battleday, Joshua C Peterson, Thomas L Griffiths
Cognitive Science
|
September 5, 2018
Evaluating (and Improving) the Correspondence Between Deep Neural Networks and Human Representations
Joshua C Peterson, Joshua T Abbott, Thomas L Griffiths
Journal of Experimental Psychology. General
|
February 22, 2024
The universal law of generalization holds for naturalistic stimuli
Raja Marjieh, Nori Jacoby, Joshua C Peterson, et al.
Nature Human Behaviour
|
June 25, 2025
Capturing the complexity of human strategic decision-making with machine learning
Jian-Qiao Zhu, Joshua C Peterson, Benjamin Enke, et al.
Journal of Experimental Psychology. General
|
April 20, 2023
Stress, intertemporal choice, and mitigation behavior during the COVID-19 pandemic
Mayank Agrawal, Joshua C Peterson, Jonathan D Cohen, et al.
Science (New York, N.Y.)
|
June 11, 2021
Using large-scale experiments and machine learning to discover theories of human decision-making
Joshua C Peterson, David D Bourgin, Mayank Agrawal, et al.
Page
of 2