Results 191 to 200 of about 1,995,230 (269)

Awake Prone Positioning in Patients With COVID-19 Respiratory Failure: A Randomized Clinical Trial.

JAMA Netw Open
Harrois A, Jouffroy R, Ayed S, Bruel C, Savale L, Devaux M, Maillet M, Cerf C, Lejealle C, Moreno CG, Levrat A, Gueneau R, Jouveshomme S, Bonnin P, De Rudnicki S, Damoisel C, Gille T, Cordel H, Meslin S, Bocquillon V, Noël N, Vieillard-Baron A, Teboul JL, Tran M, Werner M, Pichon J, Janbain A, Vicaut E, Duranteau J, PROVID Study Group.   +29 more
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Bayesian probability

Synthese, 2009
Bayesian decision theory is here construed as explicating a particular concept of rational choice and Bayesian probability is taken to be the concept of probability used in that theory. Bayesian probability is usually identified with the agent’s degrees of belief but that interpretation makes Bayesian decision theory a poor explication of the relevant ...
P. Maher
semanticscholar   +2 more sources

Bayesian Probability

Business, 2022
S. Aityan
semanticscholar   +2 more sources

Predictions of nuclear charge radii and physical interpretations based on the naive Bayesian probability classifier

, 2020
Background: The nuclear charge radii provide direct information for the nuclear structures. In recent years, many pioneering researches have been devoted to the nuclear charge radii based on the Bayesian neural networks (BNN) method.Purpose: The neural ...
Yunfei Ma, Chen Su, Jian Liu, Z. Ren, Xu, Yonghao Gao   +5 more
semanticscholar   +1 more source

Constructing Site-Specific Multivariate Probability Distribution Model Using Bayesian Machine Learning

Journal of engineering mechanics, 2019
This study proposes a novel data-driven Bayesian machine learning method for constructing site-specific multivariate probability distribution models in geotechnical engineering.
J. Ching, K. Phoon
semanticscholar   +1 more source

Epistemic uncertainty in Bayesian predictive probabilities

Journal of Biopharmaceutical Statistics, 2023
Bayesian predictive probabilities have become a ubiquitous tool for design and monitoring of clinical trials. The typical procedure is to average predictive probabilities over the prior or posterior distributions. In this paper, we highlight the limitations of relying solely on averaging, and propose the reporting of intervals or quantiles for the ...
Charles C. Liu, Ron Xiaolong Yu
openaire   +2 more sources

A RECURSION FORMULA FOR BAYESIAN PROBABILITIES

Psychological Reports, 2003
A recursion formula for Bayes' formula is derived. The formula is useful in applications in which diagnoses are added in a stepwise way to predict a criterion. On each step, changes in various diagnostic measures can be easily evaluated.
openaire   +3 more sources

Bayesian Probability Theory

2014
From the basics to the forefront of modern research, this book presents all aspects of probability theory, statistics and data analysis from a Bayesian perspective for physicists and engineers. The book presents the roots, applications and numerical implementation of probability theory, and covers advanced topics such as maximum entropy distributions ...
Linden, W., Dose, V., Toussaint, U.
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A Bayesian probability network

AIP Conference Proceedings, 1986
A model of an associative neural network is developed in which the state of each node is described by a probability density. The realization of the network is based on the pairwise joint probabilities obtained from a training set of states. A positive definite ‘‘energy’’ functional of the probabilities may be constructed from Bayes’ rule of statistical
C. H. Anderson, E. Abrahams
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