Joakim Sundh
Joakim Sundh
Researcher, Uppsala University
Verified email at - Homepage
Cited by
Cited by
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
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, 2023
Compound risk judgment in tasks with both idiosyncratic and systematic risk: The “Robust Beauty” of additive probability integration
J Sundh, P Juslin
Cognition 171, 25-41, 2018
Clarifying the relationship between coherence and accuracy in probability judgments
JQ Zhu, PWS Newall, J Sundh, N Chater, AN Sanborn
Cognition 223, 105022, 2022
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, AN Sanborn
Journal of Experimental Psychology. General. 152 (10), 2842-2860, 2023
Precise/not precise (PNP): A Brunswikian model that uses judgment error distributions to identify cognitive processes
J Sundh, A Collsiöö, P Millroth, P Juslin
Psychonomic Bulletin & Review 28, 351-373, 2021
Sampling as the human approximation to probabilistic inference
A Sanborn, JQ Zhu, J Spicer, J Sundh, P León-Villagrá, N Chater
PsyArXiv, 2021
The Cognitive Basis of Joint Probability Judgments: Processes, Ecology, and Adaption
J Sundh
Acta Universitatis Upsaliensis, 2019
An introduction to psychologically plausible sampling schemes for approximating Bayesian inference
JQ Zhu, N Chater, P León-Villagrá, J Spicer, J Sundh, A Sanborn
Sampling in Judgment and Decision Making, 467, 2023
Unpacking Intuitive and Analytic Memory Sampling in Multiple-Cue Judgment
A Collsiöö, J Sundh, P Juslin
Cambridge University Press, 2023
Capturing Asymmetric Bias in Probability Judgements
A Tee, J Sundh, A Sanborn, N Chater
Proceedings of the Annual Meeting of the Cognitive Science Society 46, 2024
Human Behavior in the Context of Low-Probability High-Impact Events
J Sundh
PsyArXiv, 2023
Approximating Bayesian inference through internal sampling
J Sundh, AN Sanborn, JQ Zhu, J Spicer, P León-Villagrá, N Chater
Cambridge University Press, 2023
The Neglected Importance of Auxiliary Assumptions when Applying Probability Theory
J Sundh
PsyArXiv, 2023
Approximation to Probabilistic
A Sanborn, JQ Zhu, J Spicer, J Sundh
Human-Like Machine Intelligence, 430, 2021
Configurative Weighting as a Two-Plane Approximation of Bayesian Estimates.
J Sundh, J Denrell
CogSci, 2020
How many instances come to mind when making probability estimates?
J Sundh, JQ Zhu, N Chater, A Sanborn
CogSci, 2020
Poker Probability Estimation
JQ Zhu, P Newall, A Sanborn, N Chater
OSF, 2019
Appreciation for Independence: Does Adaptation to Stochastic Dependence Imply Thinking According to Stochastic Principles?
J Sundh, P Juslin, P Millroth
The Ecological Scopes of Cognitive Models for Joint Probability Judgment
J Sundh
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