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ORCIDJoshua C. Peterson
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2020 – today
- 2024
[i21]Ryan Liu, Jiayi Geng, Joshua C. Peterson, Ilia Sucholutsky, Thomas L. Griffiths:
Large Language Models Assume People are More Rational than We Really are. CoRR abs/2406.17055 (2024)- [i20]Jian-Qiao Zhu, Joshua C. Peterson, Benjamin Enke, Thomas L. Griffiths:
Capturing the Complexity of Human Strategic Decision-Making with Machine Learning. CoRR abs/2408.07865 (2024) - [i19]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, Susanne Haridi, Akshay K. Jagadish, Li Ji-An, Alexander Kipnis, Sreejan Kumar, Tobias Ludwig, Marvin Mathony, Marcelo G. Mattar, Alireza Modirshanechi, Surabhi S. Nath, Joshua C. Peterson, Milena Rmus, Evan M. Russek, Tankred Saanum, Natalia Scharfenberg, Johannes A. Schubert, Luca M. Schulze Buschoff, Nishad Singhi, Xin Sui, Mirko Thalmann, Fabian J. Theis, Vuong Truong, Vishaal Udandarao, Konstantinos Voudouris, Robert Wilson, Kristin Witte, Shuchen Wu, Dirk Wulff, Huadong Xiong, Eric Schulz:
Centaur: a foundation model of human cognition. CoRR abs/2410.20268 (2024) - 2023
- [j3]Aditi Jha, Joshua C. Peterson, Thomas L. Griffiths:
Extracting Low-Dimensional Psychological Representations from Convolutional Neural Networks. Cogn. Sci. 47(1) (2023) - [c23]Joshua C. Peterson, Marina Mancoridis, Tom Griffiths:
To each their own theory: Exploring the limits of individual differences in decisions under risk. CogSci 2023 - [c22]Ilia Sucholutsky, Ruairidh M. Battleday
, Katherine M. Collins, Raja Marjieh, Joshua C. Peterson, Pulkit Singh, Umang Bhatt, Nori Jacoby, Adrian Weller, Thomas L. Griffiths:
On the informativeness of supervision signals. UAI 2023: 2036-2046 - [i18]Raja Marjieh, Nori Jacoby, Joshua C. Peterson, Thomas L. Griffiths:
The Universal Law of Generalization Holds for Naturalistic Stimuli. CoRR abs/2306.08564 (2023) - 2021
- [c21]Rachit Dubey, Joshua C. Peterson:
Combating the climate crisis with cognitive science. CogSci 2021 - 2020
- [j2]Joshua C. Peterson, Marco C. DeRuiter:
Fluorescent Nuclei Measurements Macro (FNMM), a tool for automated cell quantification in ImageJ. Softw. Impacts 6: 100030 (2020) - [c20]Aditi Jha, Joshua C. Peterson, Tom Griffiths:
Extracting low-dimensional psychological representations from convolutional neural networks. CogSci 2020 - [c19]Pulkit Singh, Joshua C. Peterson, Ruairidh M. Battleday, Tom Griffiths:
End-to-end Deep Prototype and Exemplar Models for Predicting Human Behavior. CogSci 2020 - [i17]Aditi Jha, Joshua Caleb Peterson, Thomas L. Griffiths:
Extracting low-dimensional psychological representations from convolutional neural networks. CoRR abs/2005.14363 (2020) - [i16]Pulkit Singh, Joshua C. Peterson, Ruairidh M. Battleday, Thomas L. Griffiths:
End-to-end Deep Prototype and Exemplar Models for Predicting Human Behavior. CoRR abs/2007.08723 (2020)
2010 – 2019
- 2019
- [c18]Mayank Agrawal, Joshua C. Peterson, Tom Griffiths:
Using Machine Learning to Guide Cognitive Modeling: A Case Study in Moral Reasoning. CogSci 2019: 1318-1323 - [c17]Erin Grant, Joshua C. Peterson, Tom Griffiths:
Learning deep taxonomic priors for concept learning from few positive examples. CogSci 2019: 1865-1870 - [c16]Joshua C. Peterson, Ruairidh M. Battleday, Thomas L. Griffiths, Olga Russakovsky:
Human Uncertainty Makes Classification More Robust. ICCV 2019: 9616-9625 - [c15]David D. Bourgin, Joshua C. Peterson, Daniel Reichman, Stuart J. Russell, Thomas L. Griffiths:
Cognitive model priors for predicting human decisions. ICML 2019: 5133-5141 - [i15]Mayank Agrawal, Joshua C. Peterson, Thomas L. Griffiths:
Using Machine Learning to Guide Cognitive Modeling: A Case Study in Moral Reasoning. CoRR abs/1902.06744 (2019) - [i14]Ori Plonsky, Reut Apel, Eyal Ert, Moshe Tennenholtz, David Bourgin, Joshua C. Peterson, Daniel Reichman, Thomas L. Griffiths, Stuart J. Russell, Evan C. Carter, James F. Cavanagh, Ido Erev:
Predicting human decisions with behavioral theories and machine learning. CoRR abs/1904.06866 (2019) - [i13]Ruairidh M. Battleday, Joshua C. Peterson, Thomas L. Griffiths:
Capturing human categorization of natural images at scale by combining deep networks and cognitive models. CoRR abs/1904.12690 (2019) - [i12]David D. Bourgin, Joshua C. Peterson, Daniel Reichman, Thomas L. Griffiths, Stuart J. Russell:
Cognitive Model Priors for Predicting Human Decisions. CoRR abs/1905.09397 (2019) - [i11]Joshua C. Peterson, Ruairidh M. Battleday, Thomas L. Griffiths, Olga Russakovsky:
Human uncertainty makes classification more robust. CoRR abs/1908.07086 (2019) - [i10]Mayank Agrawal, Joshua C. Peterson, Thomas L. Griffiths:
Scaling up Psychology via Scientific Regret Minimization: A Case Study in Moral Decision-Making. CoRR abs/1910.07581 (2019) - 2018
- [b1]Joshua Caleb Peterson:
Leveraging deep neural networks to study human cognition. University of California, Berkeley, USA, 2018 - [j1]Joshua C. Peterson, Joshua T. Abbott, Thomas L. Griffiths:
Evaluating (and Improving) the Correspondence Between Deep Neural Networks and Human Representations. Cogn. Sci. 42(8): 2648-2669 (2018) - [c14]Joshua C. Peterson, Jordan W. Suchow, Krisha Aghi, Alexander Y. Ku, Tom Griffiths:
Capturing human category representations by sampling in deep feature spaces. CogSci 2018 - [c13]Joshua C. Peterson, Paul Soulos, Aida Nematzadeh, Tom Griffiths:
Learning Hierarchical Visual Representations in Deep Neural Networks Using Hierarchical Linguistic Labels. CogSci 2018 - [c12]Jordan W. Suchow, Joshua C. Peterson, Tom Griffiths:
Learning a face space for experiments on human identity. CogSci 2018 - [c11]Joshua C. Peterson, Krisha Aghi, Jordan W. Suchow, Alexander Y. Ku, Tom Griffiths:
Capturing Human Category Representations by Sampling in Deep Feature Spaces. ICLR (Workshop) 2018 - [i9]Joshua C. Peterson, Jordan W. Suchow, Krisha Aghi, Alexander Y. Ku, Thomas L. Griffiths:
Capturing human category representations by sampling in deep feature spaces. CoRR abs/1805.07644 (2018) - [i8]Joshua C. Peterson, Paul Soulos, Aida Nematzadeh, Thomas L. Griffiths:
Learning Hierarchical Visual Representations in Deep Neural Networks Using Hierarchical Linguistic Labels. CoRR abs/1805.07647 (2018) - [i7]Jordan W. Suchow, Joshua C. Peterson, Thomas L. Griffiths:
Learning a face space for experiments on human identity. CoRR abs/1805.07653 (2018) - 2017
- [c10]Ruairidh M. Battleday, Joshua C. Peterson, Tom Griffiths:
Modeling human categorization of natural images using deep feature representations. CogSci 2017 - [c9]Dawn Chen, Joshua C. Peterson, Tom Griffiths:
Evaluating vector-space models of analogy. CogSci 2017 - [c8]Joshua C. Peterson, Thomas L. Griffiths:
Evidence for the size principle in semantic and perceptual domains. CogSci 2017 - [c7]Joshua C. Peterson, Joshua T. Abbott, Thomas L. Griffiths:
Adapting Deep Network Features to Capture Psychological Representations: An Abridged Report. IJCAI 2017: 4934-4938 - [i6]Joshua C. Peterson, Thomas L. Griffiths:
Evidence for the size principle in semantic and perceptual domains. CoRR abs/1705.03260 (2017) - [i5]Dawn Chen, Joshua C. Peterson, Thomas L. Griffiths:
Evaluating vector-space models of analogy. CoRR abs/1705.04416 (2017) - [i4]Joshua C. Peterson, Joshua T. Abbott, Thomas L. Griffiths:
Leveraging deep neural networks to capture psychological representations. CoRR abs/1706.02417 (2017) - [i3]Ruairidh M. Battleday, Joshua C. Peterson, Thomas L. Griffiths:
Modeling Human Categorization of Natural Images Using Deep Feature Representations. CoRR abs/1711.04855 (2017) - 2016
- [c6]Joshua C. Peterson, Joshua T. Abbott, Thomas L. Griffiths:
Adapting Deep Network Features to Capture Psychological Representations. CogSci 2016 - [c5]Steven Tang, Joshua C. Peterson, Zachary A. Pardos:
Deep Neural Networks and How They Apply to Sequential Education Data. L@S 2016: 321-324 - [i2]Joshua C. Peterson, Joshua T. Abbott, Thomas L. Griffiths:
Adapting Deep Network Features to Capture Psychological Representations. CoRR abs/1608.02164 (2016) - [i1]Steven Tang, Joshua C. Peterson, Zachary A. Pardos:
Modelling Student Behavior using Granular Large Scale Action Data from a MOOC. CoRR abs/1608.04789 (2016) - 2015
- [c4]Joshua C. Peterson, Zachary A. Pardos, Martina A. Rau, Anna Swigart, Colin Gerber, Jonathan McKinsey:
Understanding Student Success in Chemistry Using Gaze Tracking and Pupillometry. AIED 2015: 358-366 - [c3]Thomas Langlois, Joshua C. Peterson, Stephen E. Palmer:
The colors and textures of musical sounds. CogSci 2015 - [c2]Joshua C. Peterson, Stephen E. Palmer:
Emotionally mediated crossmodal correspondences affect classification performance. CogSci 2015 - [c1]Rachit Dubey, Joshua C. Peterson, Aditya Khosla, Ming-Hsuan Yang, Bernard Ghanem:
What Makes an Object Memorable? ICCV 2015: 1089-1097
Coauthor Index
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