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Joshua C. Peterson · SciRah

Researcher profile · Semantic Scholar

Joshua C. Peterson

Princeton University

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Joshua C. Peterson — researcher profile on SciRah

ORCID iD 0000-0001-6713-1353Homepage

h-index: 20
Works: 49
Citations: 1,954

Most-cited papers

Human Uncertainty Makes Classification More Robust
Joshua C. Peterson, R. Battleday, T. Griffiths, O. Russakovsky
2019IEEE International Conference on Computer Vision420 citations Open access
Semantic Scholar
Using large-scale experiments and machine learning to discover theories of human decision-making
Joshua C. Peterson, David D. Bourgin, Mayank Agrawal, Daniel Reichman +1 more
2021Science250 citations
Semantic Scholar
Evaluating (and Improving) the Correspondence Between Deep Neural Networks and Human Representations
Joshua C. Peterson, Joshua T. Abbott, T. Griffiths
2017Cognitive Sciences166 citations Open access
Semantic Scholar
Capturing human categorization of natural images by combining deep networks and cognitive models
R. Battleday, Joshua C. Peterson, T. Griffiths
2020Nature Communications117 citations Open access
Semantic Scholar
What Makes an Object Memorable?
Rachit Dubey, Joshua C. Peterson, A. Khosla, Ming-Hsuan Yang +1 more
2015IEEE International Conference on Computer Vision111 citations
Semantic Scholar
Cognitive Model Priors for Predicting Human Decisions
David D. Bourgin, Joshua C. Peterson, Daniel Reichman, T. Griffiths +1 more
2019International Conference on Machine Learning94 citations
Semantic Scholar
Deep models of superficial face judgments
Joshua C. Peterson, Stefan Uddenberg, T. Griffiths, Alexander T. Todorov +1 more
2022Proceedings of the National Academy of Sciences of the United States of America76 citations Open access
Semantic Scholar
Adapting Deep Network Features to Capture Psychological Representations
Joshua C. Peterson, Joshua T. Abbott, T. Griffiths
2016Annual Meeting of the Cognitive Science Society76 citations
Semantic Scholar
Large Language Models Assume People are More Rational than We Really are
Ryan Liu, Jia-Yi Geng, Joshua C. Peterson, Ilia Sucholutsky +1 more
2024International Conference on Learning Representations70 citations
Semantic Scholar
Scaling up psychology via Scientific Regret Minimization
Mayank Agrawal, Joshua C. Peterson, T. Griffiths
2020Proceedings of the National Academy of Sciences of the United States of America66 citations Open access
Semantic Scholar
Centaur: a foundation model of human cognition
Marcel Binz, Elif Akata, Matthias Bethge, Franziska Brändle +37 more
2024arXiv.org60 citations
Semantic Scholar
Predicting human decisions with behavioral theories and machine learning
Ori Plonsky, Reut Apel, E. Ert, Moshe Tennenholtz +8 more
2019arXiv.org53 citations
Semantic Scholar
Evaluating vector-space models of analogy
Dawn Chen, Joshua C. Peterson, T. Griffiths
2017Annual Meeting of the Cognitive Science Society52 citations
Semantic Scholar
Deep Neural Networks and How They Apply to Sequential Education Data
Steven Tang, Joshua C. Peterson, Z. Pardos
2016ACM Conference on Learning @ Scale52 citations
Semantic Scholar
From convolutional neural networks to models of higher‐level cognition (and back again)
R. Battleday, Joshua C. Peterson, T. Griffiths
2021Annals of the New York Academy of Sciences38 citations Open access
Semantic Scholar
Parallelograms revisited: Exploring the limitations of vector space models for simple analogies.
Joshua C. Peterson, Dawn Chen, T. Griffiths
2020Cognition34 citations Open access
Semantic Scholar
Capturing the complexity of human strategic decision-making with machine learning
Jian-Qiao Zhu, Joshua C. Peterson, Ben Enke, Thomas L. Griffiths
2024Nature Human Behaviour23 citations
Semantic Scholar
Modeling human categorization of natural images using deep feature representations
R. Battleday, Joshua C. Peterson, T. Griffiths
2017Annual Meeting of the Cognitive Science Society22 citations
Semantic Scholar
On the Informativeness of Supervision Signals
Ilia Sucholutsky, R. Battleday, Katherine M. Collins, Raja Marjieh +6 more
2022Conference on Uncertainty in Artificial Intelligence21 citations Open access
Semantic Scholar
End-to-end Deep Prototype and Exemplar Models for Predicting Human Behavior
Pulkit Singh, Joshua C. Peterson, R. Battleday, T. Griffiths
2020Annual Meeting of the Cognitive Science Society21 citations
Semantic Scholar
Adapting Deep Network Features to Capture Psychological Representations: An Abridged Report
Joshua C. Peterson, Joshua T. Abbott, Thomas L. Griffiths
2017International Joint Conference on Artificial Intelligence20 citations Open access
Semantic Scholar
Modelling Student Behavior using Granular Large Scale Action Data from a MOOC
Steven Tang, Joshua C. Peterson, Z. Pardos
2016arXiv.org19 citations
Semantic Scholar
Understanding Student Success in Chemistry Using Gaze Tracking and Pupillometry
Joshua C. Peterson, Z. Pardos, M. Rau, Anna Swigart +2 more
2015International Conference on Artificial Intelligence in Education18 citations
Semantic Scholar
Capturing human categorization of natural images at scale by combining deep networks and cognitive models
R. Battleday, Joshua C. Peterson, T. Griffiths
2019arXiv.org16 citations
Semantic Scholar
Learning Hierarchical Visual Representations in Deep Neural Networks Using Hierarchical Linguistic Labels
Joshua C. Peterson, Paul Soulos, Aida Nematzadeh, T. Griffiths
2018Annual Meeting of the Cognitive Science Society14 citations
Semantic Scholar
Using Machine Learning to Guide Cognitive Modeling: A Case Study in Moral Reasoning
Mayank Agrawal, Joshua C. Peterson, T. Griffiths
2019Annual Meeting of the Cognitive Science Society12 citations
Semantic Scholar
Learning a face space for experiments on human identity
J. Suchow, Joshua C. Peterson, T. Griffiths
2018Annual Meeting of the Cognitive Science Society8 citations
Semantic Scholar
The Universal Law of Generalization Holds for Naturalistic Stimuli
Raja Marjieh, Nori Jacoby, Joshua C. Peterson, T. Griffiths
2023Journal of experimental psychology. General7 citations Open access
Semantic Scholar
Learning deep taxonomic priors for concept learning from few positive examples
Erin Grant, Joshua C. Peterson, Tom Griffiths
2019Annual Meeting of the Cognitive Science Society5 citations
Semantic Scholar
Capturing human category representations by sampling in deep feature spaces
Joshua C. Peterson, J. Suchow, Krisha Aghi, Alexander Ku +1 more
2018International Conference on Learning Representations4 citations
Semantic Scholar
Machine learning for modeling human decisions.
Daniel Reichman, Joshua C. Peterson, Thomas L. Griffiths
2024Decision3 citations
Semantic Scholar
Data-Driven, Photorealistic Social Face-Trait Encoding, Prediction, and Manipulation Using Deep Neural Networks
A. Todorov, Stefan Uddenberg, Joshua C. Peterson, T. Griffiths +1 more
20203 citations
Semantic Scholar
Evidence for the size principle in semantic and perceptual domains
Joshua C. Peterson, T. Griffiths
2017Annual Meeting of the Cognitive Science Society3 citations
Semantic Scholar
Scaling up Psychology via Scientific Regret Minimization: A Case Study in Moral Decisions
Mayank Agrawal, Joshua C. Peterson, T. Griffiths
20192 citations
Semantic Scholar
A learned generative model of faces for experiments on human identity
J. Suchow, Joshua C. Peterson, T. Griffiths
2018Journal of Vision2 citations Open access
Semantic Scholar
Journal of Experimental Psychology: General Stress, Intertemporal Choice, and Mitigation Behavior During the COVID-19 Pandemic
Mayank Agrawal, Joshua C. Peterson, J. Cohen, T. Grif +1 more
2 citations
Semantic Scholar
Combating the climate crisis with cognitive science
Rachit Dubey, Joshua C. Peterson
2021Annual Meeting of the Cognitive Science Society1 citations
Semantic Scholar
Capturing and modifying the perceived traits of all possible faces
Joshua C. Peterson, Stefan Uddenberg, Tom Griffiths, Alexander T. Todorov +1 more
20211 citations Open access
Semantic Scholar
Learning to generalize like humans using basic-level object labels
Joshua C. Peterson, Paul Soulos, Aida Nematzadeh, T. Griffiths
2019Journal of Vision1 citations Open access
Semantic Scholar
Improving machine classification using human uncertainty measurements
R. Battleday, Joshua C. Peterson, T. Griffiths
20181 citations
Semantic Scholar
Sampling from object and scene representations using deep feature spaces
Joshua C. Peterson, Krisha Aghi, J. Suchow, Alexander Ku +1 more
2018Journal of Vision1 citations Open access
Semantic Scholar
Intertemporal choice under stress: an ongoing study during the COVID-19 pandemic
Joshua C. Peterson, Mayank Agrawal, R. Jansen, T. Sumers +3 more
20200 citations
Semantic Scholar
Integrating a Gaussian Classifier into a CNN
Pulkit Singh, Joshua C. Peterson, R. Battleday
20190 citations
Semantic Scholar
Human uncertainty improves object classification
Joshua C. Peterson, R. Battleday, T. Griffiths
20192019 Conference on Cognitive Computational Neuroscience0 citations Open access
Semantic Scholar
Scaling up Psychology via Scientific Regret Minimization: A Case Study in Moral Decision-Making
Mayank Agrawal, Joshua C. Peterson, T. Griffiths
2019arXiv.org0 citations
Semantic Scholar
Using features from deep neural networks to model human categorization of natural images
R. Battleday, Joshua C. Peterson, T. Griffiths
20180 citations
Semantic Scholar
Leveraging deep neural networks to capture psychological representations
Joshua C. Peterson, Joshua T. Abbott, T. Griffiths
2017arXiv.org0 citations
Semantic Scholar
Proceedings of the Annual Meeting of the Cognitive Science Society
Joshua C. Peterson, Marina Mancoridis, Thomas L. Griffiths
0 citations
Semantic Scholar
Models Don’t Know What You Want: Evaluating Personalization in Deep Research Needs Real Users . Association for Computational Linguistics
Nishant Balepur, Malachi Hamada, V. Kishore, Sergey Feldman +355 more
0 citations
Semantic Scholar

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