Results 21 to 30 of about 5,701,088 (332)
Effect of prior probability quality on biased time-delay estimation. [PDF]
Ultrason Imaging, 2012 Byram BC, Trahey GE, Palmeri ML.
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The probability flow ODE is provably fast [PDF]
Neural Information Processing Systems, 2023 We provide the first polynomial-time convergence guarantees for the probability flow ODE implementation (together with a corrector step) of score-based generative modeling.
Sitan Chen +5 more
semanticscholar +1 more source
Estimating statistical power, posterior probability and publication bias of psychological research using the observed replication rate [PDF]
Royal Society Open Science, 2018 In this paper, we show how Bayes' theorem can be used to better understand the implications of the 36% reproducibility rate of published psychological findings reported by the Open Science Collaboration. We demonstrate a method to assess publication bias
Michael Ingre, Gustav Nilsonne
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Probabilistic machine learning for breast cancer classification
Mathematical Biosciences and Engineering, 2023 A probabilistic neural network has been implemented to predict the malignancy of breast cancer cells, based on a data set, the features of which are used for the formulation and training of a model for a binary classification problem. The focus is placed
Anastasia-Maria Leventi-Peetz, Kai Weber
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Consistency of mixture models with a prior on the number of components [PDF]
Dependence Modeling, 2022 This article establishes general conditions for posterior consistency of Bayesian finite mixture models with a prior on the number of components. That is, we provide sufficient conditions under which the posterior concentrates on neighborhoods of the ...
Jeffrey W. Miller
semanticscholar +1 more source
A Bayesian Inference Based Computational Tool for Parametric and Nonparametric Medical Diagnosis
Diagnostics, 2023 Medical diagnosis is the basis for treatment and management decisions in healthcare. Conventional methods for medical diagnosis commonly use established clinical criteria and fixed numerical thresholds. The limitations of such an approach may result in a
Theodora Chatzimichail +1 more
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Modelling decision-making biases
Frontiers in Computational Neuroscience, 2023 Biases are a fundamental aspect of everyday life decision-making. A variety of modelling approaches have been suggested to capture decision-making biases.
Ettore Cerracchio +2 more
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Conditional probability and improper priors [PDF]
Communications in Statistics - Theory and Methods, 2016 The purpose of this paper is to present a mathematical theory that can be used as a foundation for statistics that include improper priors. This theory includes improper laws in the initial axioms and has in particular Bayes theorem as a consequence. Another consequence is that some of the usual calculation rules are modified.
Bo Henry Lindqvist, Gunnar Taraldsen
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Update of Prior Probabilities by Minimal Divergence [PDF]
Entropy, 2021 The present paper investigates the update of an empirical probability distribution with the results of a new set of observations. The update reproduces the new observations and interpolates using prior information. The optimal update is obtained by minimizing either the Hellinger distance or the quadratic Bregman divergence. The results obtained by the
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