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Etymologia: Bayesian Probability [PDF]
Emerging Infectious Diseases, 2017 Ronnie Henry, Martin I. Meltzer
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Bayesian optimization for computationally extensive probability distributions. [PDF]
PLoS ONE, 2018 An efficient method for finding a better maximizer of computationally extensive probability distributions is proposed on the basis of a Bayesian optimization technique.
Ryo Tamura, Koji Hukushima
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A categorical foundation for Bayesian probability [PDF]
Applied Categorical Structures, 2013 Given two measurable spaces $H$ and $D$ with countably generated $\sigma$-algebras, a perfect prior probability measure $P_H$ on $H$ and a sampling distribution $S: H \rightarrow D$, there is a corresponding inference map $I: D \rightarrow H$ which is ...
A Kock +13 more
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Cognitive biases as Bayesian probability weighting in context [PDF]
Frontiers in PsychologyIntroductionHumans often exhibit systematic biases in judgments under uncertainty, such as conservatism bias and base-rate neglect. This study investigates the context dependence of these biases within a Bayesian framework.MethodsForty-eight participants
Bruno Kopp
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Probability biases as Bayesian inference [PDF]
Judgment and Decision Making, 2006 In this article, I will show how several observed biases in human probabilistic reasoning can be partially explained as good heuristics for making inferences in an environment where probabilities have uncertainties associated to them.
André C. R. Martins
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暴雨灾害, 2021 Using the historical precipitation observation data in the Haihe River Basin and the ECMWF ensemble prediction, the 289 grid points in the Haihe River Basin are modeled with Bayesian Processor of Output (BPO), which revise the determine precipitation ...
Shu XU, Mingming XIONG, Fajing CHEN
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Bayesian Brains without Probabilities [PDF]
Trends in Cognitive Sciences, 2016 Bayesian explanations have swept through cognitive science over the past two decades, from intuitive physics and causal learning, to perception, motor control and language. Yet people flounder with even the simplest probability questions. What explains this apparent paradox? How can a supposedly Bayesian brain reason so poorly with probabilities?
Sanborn, Adam N., Chater, Nick
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The research on Bayesian inference for geophysical inversion
地球与行星物理论评, 2022 Based on statistical theory, the Bayesian inversion method adopts the posterior probability distribution to evaluate the model parameters under the constraints of prior information and observation data.
Xingda Jiang, Wei Zhang, Hui Yang
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Quantum probabilities as Bayesian probabilities [PDF]
Physical Review A, 2002 In the Bayesian approach to probability theory, probability quantifies a degree of belief for a single trial, without any a priori connection to limiting frequencies. In this paper we show that, despite being prescribed by a fundamental law, probabilities for individual quantum systems can be understood within the Bayesian approach.
Caves, Carlton M. +2 more
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The Bayesian sampler : generic Bayesian inference causes incoherence in human probability [PDF]
, 2020 Human probability judgments are systematically biased, in apparent tension with Bayesian models of cognition. But perhaps the brain does not represent probabilities explicitly, but approximates probabilistic calculations through a process of sampling, as
Chater, Nick +2 more
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