Joshua C. Peterson

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Thomas L. GriffithsProfessor of Psychology and Computer Science, Princeton UniversityVerified email at princeton.edu
Ruairidh McLennan BattledayPhD Candidate, Princeton UniversityVerified email at princeton.edu
Joshua T. AbbottMelbourne School of Psychological SciencesVerified email at unimelb.edu.au
Zachary A. PardosAssociate Professor at UC BerkeleyVerified email at berkeley.edu
Rachit DubeyGraduate student, Princeton UniversityVerified email at berkeley.edu
David D BourginUniversity of California BerkeleyVerified email at berkeley.edu
Daniel ReichmanWorcester Polytechnic InstituteVerified email at wpi.edu
Jordan SuchowStevens Institute of TechnologyVerified email at stevens.edu
Bernard GhanemAssociate Professor, King Abdullah University of Science and TechnologyVerified email at kaust.edu.sa
Stuart RussellProfessor of Computer Science, University of California, BerkeleyVerified email at cs.berkeley.edu
Dawn ChenUniversity of California, BerkeleyVerified email at berkeley.edu
Mayank AgrawalPrinceton UniversityVerified email at princeton.edu
Ming-Hsuan YangProfessor, University of California at Merced; Research Scientist, GoogleVerified email at ucmerced.edu
Aditya KhoslaCo-founder and CTO, PathAIVerified email at pathai.com
Olga RussakovskyAssistant Professor, Princeton UniversityVerified email at cs.princeton.edu
Ori PlonskyAssistant Professor, Technion - Israel Institute of TechnologyVerified email at technion.ac.il
Ido ErevProfessor of Behavioral Science, TechnionVerified email at tx.technion.ac.il
Evan C CarterU.S. Army Research LaboratoryVerified email at mail.mil
Moshe TennenholtzVerified email at ie.technion.ac.il
Eyal ErtAssociate Professor, Hebrew University of JerusalemVerified email at mail.huji.ac.il

Joshua C. Peterson

Princeton University

Verified email at princeton.edu - Homepage

Cognitive Science Machine Learning Artificial Intelligence


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
What makes an object memorable? R Dubey, J Peterson, A Khosla, MH Yang, B Ghanem Proceedings of the ieee international conference on computer vision, 1089-1097, 2015	86	2015
Adapting deep network features to capture psychological representations JC Peterson, JT Abbott, TL Griffiths arXiv preprint arXiv:1608.02164, 2016	68*	2016
Human uncertainty makes classification more robust JC Peterson, RM Battleday, TL Griffiths, O Russakovsky Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019	63*	2019
Evaluating (and Improving) the Correspondence Between Deep Neural Networks and Human Representations JC Peterson, JT Abbott, TL Griffiths Cognitive Science 42 (8), 2648-2669, 2018	60	2018
Evaluating vector-space models of analogy D Chen, JC Peterson, TL Griffiths arXiv preprint arXiv:1705.04416, 2017	54	2017
Cognitive model priors for predicting human decisions J Peterson, D Bourgin, D Reichman, S Russell, T Griffiths International Conference on Machine Learning, 5133-5141, 2019	41*	2019
Deep neural networks and how they apply to sequential education data S Tang, JC Peterson, ZA Pardos Proceedings of the Third (2016) ACM Conference on Learning@ Scale, 321-324, 2016	38	2016
Predicting human decisions with behavioral theories and machine learning O Plonsky, R Apel, E Ert, M Tennenholtz, D Bourgin, JC Peterson, ... arXiv preprint arXiv:1904.06866, 2019	32	2019
Capturing human categorization of natural images by combining deep networks and cognitive models RM Battleday, JC Peterson, TL Griffiths Nature communications 11 (1), 1-14, 2020	20	2020
Modelling student behavior using granular large scale action data from a MOOC S Tang, JC Peterson, ZA Pardos arXiv preprint arXiv:1608.04789, 2016	16	2016
Understanding Student Success in Chemistry using Gaze Tracking & Pupillometry J Peterson, Z Pardos, M Rau, A Swigart, C Gerber, J McKinsey Artificial Intelligence in Education, 2015	16	2015
Modeling human categorization of natural images using deep feature representations RM Battleday, JC Peterson, TL Griffiths arXiv preprint arXiv:1711.04855, 2017	15	2017
Scaling up psychology via scientific regret minimization M Agrawal, JC Peterson, TL Griffiths Proceedings of the National Academy of Sciences 117 (16), 8825-8835, 2020	12	2020
Using large-scale experiments and machine learning to discover theories of human decision-making JC Peterson, DD Bourgin, M Agrawal, D Reichman, TL Griffiths Science 372 (6547), 1209-1214, 2021	11	2021
Predictive modelling of student behaviour using granular large-scale action data S Tang, J Peterson, Z Pardos The Handbook of Learning Analytics, 223-233, 2017	11	2017
Using machine learning to guide cognitive modeling: A case study in moral reasoning M Agrawal, JC Peterson, TL Griffiths arXiv preprint arXiv:1902.06744, 2019	10	2019
Learning hierarchical visual representations in deep neural networks using hierarchical linguistic labels JC Peterson, P Soulos, A Nematzadeh, TL Griffiths arXiv preprint arXiv:1805.07647, 2018	10	2018
Learning a face space for experiments on human identity JW Suchow, JC Peterson, TL Griffiths arXiv preprint arXiv:1805.07653, 2018	5	2018
Parallelograms revisited: Exploring the limitations of vector space models for simple analogies JC Peterson, D Chen, TL Griffiths Cognition 205, 104440, 2020	4	2020
End-to-end deep prototype and exemplar models for predicting human behavior P Singh, JC Peterson, RM Battleday, TL Griffiths arXiv preprint arXiv:2007.08723, 2020	4	2020

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