Understanding Student Success in Chemistry Using Gaze Tracking and Pupillometry. - Joshua C. Peterson; Zachary A. Pardos; Martina A. Rau; Anna Swigart; Colin Gerber; Jonathan McKinsey (AIED, 2015)

The colors and textures of musical sounds. - Thomas Langlois; Joshua C. Peterson; Stephen E. Palmer (CogSci, 2015)

Emotionally mediated crossmodal correspondences affect classification performance. - Joshua C. Peterson; Stephen E. Palmer (CogSci, 2015)

What Makes an Object Memorable? - Rachit Dubey; Joshua C. Peterson; Aditya Khosla; Ming-Hsuan Yang 001; Bernard Ghanem (ICCV, 2015)

Adapting Deep Network Features to Capture Psychological Representations. - Joshua C. Peterson; Joshua T. Abbott; Thomas L. Griffiths 001 (CogSci, 2016)

Deep Neural Networks and How They Apply to Sequential Education Data. - Steven Tang; Joshua C. Peterson; Zachary A. Pardos (L@S, 2016)

Modelling Student Behavior using Granular Large Scale Action Data from a MOOC. - Steven Tang; Joshua C. Peterson; Zachary A. Pardos (CoRR, 2016)

Modeling human categorization of natural images using deep feature representations. - Ruairidh M. Battleday; Joshua C. Peterson; Tom Griffiths 001 (CogSci, 2017)

Evaluating vector-space models of analogy. - Dawn Chen; Joshua C. Peterson; Tom Griffiths 001 (CogSci, 2017)

Evidence for the size principle in semantic and perceptual domains. - Joshua C. Peterson; Thomas L. Griffiths 001 (CogSci, 2017)

Adapting Deep Network Features to Capture Psychological Representations: An Abridged Report. - Joshua C. Peterson; Joshua T. Abbott; Thomas L. Griffiths 001 (IJCAI, 2017)

Leveraging deep neural networks to capture psychological representations. - Joshua C. Peterson; Joshua T. Abbott; Thomas L. Griffiths 001 (CoRR, 2017)

Learning Hierarchical Visual Representations in Deep Neural Networks Using Hierarchical Linguistic Labels. - Joshua C. Peterson; Paul Soulos; Aida Nematzadeh; Tom Griffiths 001 (CogSci, 2018)

Learning a face space for experiments on human identity. - Jordan W. Suchow; Joshua C. Peterson; Tom Griffiths 001 (CogSci, 2018)

Capturing Human Category Representations by Sampling in Deep Feature Spaces. - Joshua C. Peterson; Krisha Aghi; Jordan W. Suchow; Alexander Y. Ku; Tom Griffiths 001 (ICLR (Workshop), 2018)

Evaluating (and Improving) the Correspondence Between Deep Neural Networks and Human Representations. - Joshua C. Peterson; Joshua T. Abbott; Thomas L. Griffiths 001 (Cogn. Sci., 2018)

Leveraging deep neural networks to study human cognition. - Joshua Caleb Peterson (2018)

Using Machine Learning to Guide Cognitive Modeling: A Case Study in Moral Reasoning. - Mayank Agrawal; Joshua C. Peterson; Tom Griffiths 001 (CogSci, 2019)

Learning deep taxonomic priors for concept learning from few positive examples. - Erin Grant; Joshua C. Peterson; Tom Griffiths 001 (CogSci, 2019)

Human Uncertainty Makes Classification More Robust. - Joshua C. Peterson; Ruairidh M. Battleday; Thomas L. Griffiths 001; Olga Russakovsky (ICCV, 2019)

Cognitive model priors for predicting human decisions. - David D. Bourgin; Joshua C. Peterson; Daniel Reichman 001; Stuart J. Russell; Thomas L. Griffiths 001 (ICML, 2019)

Predicting human decisions with behavioral theories and machine learning. - Ori Plonsky; Reut Apel; Eyal Ert; Moshe Tennenholtz; David Bourgin; Joshua C. Peterson; Daniel Reichman 001; Thomas L. Griffiths 001; Stuart J. Russell; Evan C. Carter; James F. Cavanagh; Ido Erev (CoRR, 2019)

Capturing human categorization of natural images at scale by combining deep networks and cognitive models. - Ruairidh M. Battleday; Joshua C. Peterson; Thomas L. Griffiths 001 (CoRR, 2019)

Scaling up Psychology via Scientific Regret Minimization: A Case Study in Moral Decision-Making. - Mayank Agrawal; Joshua C. Peterson; Thomas L. Griffiths 001 (CoRR, 2019)

End-to-end Deep Prototype and Exemplar Models for Predicting Human Behavior. - Pulkit Singh; Joshua C. Peterson; Ruairidh M. Battleday; Tom Griffiths 001 (CogSci, 2020)

Fluorescent Nuclei Measurements Macro (FNMM), a tool for automated cell quantification in ImageJ. - Joshua C. Peterson; Marco C. DeRuiter (Softw. Impacts, 2020)

Combating the climate crisis with cognitive science. - Rachit Dubey; Joshua C. Peterson (CogSci, 2021)

To each their own theory: Exploring the limits of individual differences in decisions under risk. - Joshua C. Peterson; Marina Mancoridis; Tom Griffiths 001 (CogSci, 2023)

On the informativeness of supervision signals. - Ilia Sucholutsky; Ruairidh M. Battleday; Katherine M. Collins; Raja Marjieh; Joshua C. Peterson; Pulkit Singh; Umang Bhatt; Nori Jacoby; Adrian Weller; Thomas L. Griffiths 001 (UAI, 2023)

The Universal Law of Generalization Holds for Naturalistic Stimuli. - Raja Marjieh; Nori Jacoby; Joshua C. Peterson; Thomas L. Griffiths 001 (CoRR, 2023)

Extracting Low-Dimensional Psychological Representations from Convolutional Neural Networks. - Aditi Jha; Joshua C. Peterson; Thomas L. Griffiths 001 (Cogn. Sci., 2023)

Capturing the Complexity of Human Strategic Decision-Making with Machine Learning. - Jian-Qiao Zhu; Joshua C. Peterson; Benjamin Enke; Thomas L. Griffiths 001 (CoRR, 2024)

Centaur: a foundation model of human cognition. - Marcel Binz; Elif Akata; Matthias Bethge; Franziska Brändle; Fred Callaway; Julian Coda-Forno; Peter Dayan; Can Demircan; Maria K. Eckstein; Noémi Élteto; Thomas L. Griffiths 001; Susanne Haridi; et al. (CoRR, 2024)

Large Language Models Assume People are More Rational than We Really are. - Ryan Liu 001; Jiayi Geng; Joshua C. Peterson; Ilia Sucholutsky; Thomas L. Griffiths 001 (ICLR, 2025)