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 | 56 | 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 | 15 | 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 | 10 | 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 | 9 | 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 | 6* | 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 | 6 | 2021 |

Sampling as the human approximation to probabilistic inference A Sanborn, JQ Zhu, J Spicer, J Sundh, P León-Villagrá, N Chater PsyArXiv, 2021 | 5 | 2021 |

The Cognitive Basis of Joint Probability Judgments: Processes, Ecology, and Adaption J Sundh Acta Universitatis Upsaliensis, 2019 | 3 | 2019 |

Kahneman in quotes and reflections B Buttliere, A Arvanitis, M Białek, S Choshen-Hillel, S Davidai, T Gilovich, ... Psychological Inquiry 35 (1), 3-10, 2024 | 1 | 2024 |

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 | 1 | 2023 |

Unpacking Intuitive and Analytic Memory Sampling in Multiple-Cue Judgment A Collsiöö, J Sundh, P Juslin Cambridge University Press, 2023 | 1 | 2023 |

Human behavior in the context of low-probability high-impact events J Sundh Humanities and Social Sciences Communications 11 (1), 1-10, 2024 | | 2024 |

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 | | 2024 |

Approximating Bayesian inference through internal sampling J Sundh, AN Sanborn, JQ Zhu, J Spicer, P León-Villagrá, N Chater Cambridge University Press, 2023 | | 2023 |

The Neglected Importance of Auxiliary Assumptions when Applying Probability Theory J Sundh PsyArXiv, 2023 | | 2023 |

Approximation to Probabilistic A Sanborn, JQ Zhu, J Spicer, J Sundh Human-Like Machine Intelligence, 430, 2021 | | 2021 |

Configurative Weighting as a Two-Plane Approximation of Bayesian Estimates. J Sundh, J Denrell CogSci, 2020 | | 2020 |

How many instances come to mind when making probability estimates? J Sundh, JQ Zhu, N Chater, A Sanborn CogSci, 2020 | | 2020 |

Poker Probability Estimation JQ Zhu, P Newall, A Sanborn, N Chater OSF, 2019 | | 2019 |

Appreciation for Independence: Does Adaptation to Stochastic Dependence Imply Thinking According to Stochastic Principles? J Sundh, P Juslin, P Millroth | | 2019 |