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Jian-Qiao Zhu
Jian-Qiao Zhu
Department of Computer Science, Princeton University
Verified email at princeton.edu - Homepage
Title
Cited by
Cited by
Year
The Bayesian sampler: Generic Bayesian inference causes incoherence in human probability judgments.
JQ Zhu, AN Sanborn, N Chater
Psychological review 127 (5), 719, 2020
1332020
Costly curiosity: People pay a price to resolve an uncertain gamble early
JAMR Cabrero, JQ Zhu, EA Ludvig
Behavioural Processes 160, 20-25, 2019
722019
Probabilistic biases meet the Bayesian brain
N Chater, JQ Zhu, J Spicer, J Sundh, P León-Villagrá, A Sanborn
Current Directions in Psychological Science 29 (5), 506-512, 2020
712020
Mental sampling in multimodal representations
JQ Zhu, AN Sanborn, N Chater
Advances in Neural Information Processing Systems, 5748-5759, 2018
452018
Information seeking as chasing anticipated prediction errors.
JQ Zhu, W Xiang, EA Ludvig
Proceedings of the 39th Annual Meeting of the Cognitive Science Society …, 2017
272017
The autocorrelated Bayesian sampler: A rational process for probability judgments, estimates, confidence intervals, choices, confidence judgments, and response times.
JQ Zhu, J Sundh, J Spicer, N Chater, AN Sanborn
Psychological review 131 (2), 456, 2024
202024
A unified explanation of variability and bias in human probability judgments: How computational noise explains the mean–variance signature.
J Sundh, JQ Zhu, N Chater, A Sanborn
Journal of Experimental Psychology: General 152 (10), 2842, 2023
14*2023
Understanding the structure of cognitive noise
JQ Zhu, P León-Villagrá, N Chater, AN Sanborn
PLoS computational biology 18 (8), e1010312, 2022
132022
Bayes in the age of intelligent machines
TL Griffiths, JQ Zhu, E Grant, R Thomas McCoy
Current Directions in Psychological Science 33 (5), 283-291, 2024
122024
Clarifying the relationship between coherence and accuracy in probability judgments
JQ Zhu, PWS Newall, J Sundh, N Chater, AN Sanborn
Cognition 223, 105022, 2022
122022
Perceptual and Cognitive Judgments Show Both Anchoring and Repulsion
J Spicer, JQ Zhu, N Chater, AN Sanborn
Psychological Science 33, 323-335, 2022
112022
Noise in cognition: Bug or feature?
AN Sanborn, JQ Zhu, J Spicer, P León-Villagrá, L Castillo, JK Falbén, ...
Perspectives on Psychological Science, 17456916241258951, 2024
92024
Deep de finetti: Recovering topic distributions from large language models
L Zhang, RT McCoy, TR Sumers, JQ Zhu, TL Griffiths
arXiv preprint arXiv:2312.14226, 2023
82023
Capturing the complexity of human strategic decision-making with machine learning
JQ Zhu, JC Peterson, B Enke, TL Griffiths
arXiv preprint arXiv:2408.07865, 2024
72024
Incoherent probability judgments in large language models
JQ Zhu, TL Griffiths
arXiv preprint arXiv:2401.16646, 2024
62024
Recovering mental representations from large language models with markov chain monte carlo
JQ Zhu, H Yan, TL Griffiths
arXiv preprint arXiv:2401.16657, 2024
62024
Sampling as the Human Approximation to Probabilistic Inference.
A Sanborn, JQ Zhu, J Spicer, J Sundh, P León-Villagrá, N Chater
Human-like machine intelligence, 430-448, 2022
62022
How do people predict a random walk? Lessons for models of human cognition.
J Spicer, JQ Zhu, N Chater, AN Sanborn
Psychological Review, 2024
52024
Eliciting the priors of large language models using iterated in-context learning
JQ Zhu, TL Griffiths
arXiv preprint arXiv:2406.01860, 2024
52024
Cognitive variability matches speculative price dynamics
JQ Zhu, J Spicer, A Sanborn, N Chater
OSF, 2021
42021
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Articles 1–20