Joshua C. Peterson
Joshua C. Peterson
Verifierad e-postadress på princeton.edu - Startsida
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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
862015
Adapting deep network features to capture psychological representations
JC Peterson, JT Abbott, TL Griffiths
arXiv preprint arXiv:1608.02164, 2016
71*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
69*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
612018
Evaluating vector-space models of analogy
D Chen, JC Peterson, TL Griffiths
arXiv preprint arXiv:1705.04416, 2017
562017
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
45*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
392016
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
332019
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
222020
Modelling student behavior using granular large scale action data from a MOOC
S Tang, JC Peterson, ZA Pardos
arXiv preprint arXiv:1608.04789, 2016
162016
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
162015
Modeling human categorization of natural images using deep feature representations
RM Battleday, JC Peterson, TL Griffiths
arXiv preprint arXiv:1711.04855, 2017
152017
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
132020
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
122021
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
112017
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
102019
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
102018
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
52020
Learning a face space for experiments on human identity
JW Suchow, JC Peterson, TL Griffiths
arXiv preprint arXiv:1805.07653, 2018
52018
From convolutional neural networks to models of higher‐level cognition (and back again)
RM Battleday, JC Peterson, TL Griffiths
Annals of the New York Academy of Sciences, 2021
42021
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Artiklar 1–20