Results 221 to 230 of about 166,561 (260)

Bayesian Approach to Probability

2016
The Bayesian approach to probability allows to define in a quantitative way probabilities associated to statement whose truth or falsity is not known. This also applies to the knowledge of unknown parameters in physics, allowing to assign a probability to the possibility that a parameter’s value lies within a certain interval.
openaire   +1 more source

Recent Advances in Bayesian Optimization

ACM Computing Surveys, 2023
Xilu Wang, Yaochu Jin, Sebastian Schmitt   +2 more
exaly  

Probability and Bayesian Statistics.

The Statistician, 1989
P. M. Lee, R. Viertl
openaire   +2 more sources

Bayesian Probability

2022
openaire   +1 more source

Bayesian learning for neural networks: an algorithmic survey

Artificial Intelligence Review, 2023
Alexandros Iosifidis, Iosifidis Alexandros   +1 more
exaly  

Bayesian Probability

1993
Paul Krause, Dominic Clark
openaire   +1 more source

The JASP guidelines for conducting and reporting a Bayesian analysis

Psychonomic Bulletin and Review, 2020
Don Van Den Bergh, Fabian Dablander, Koen Derks   +2 more
exaly  

Discrete Bayesian Network Classifiers

ACM Computing Surveys, 2014
Concha Bielza, Pedro Larranaga
exaly  

Visualization in Bayesian Workflow

Journal of the Royal Statistical Society Series A: Statistics in Society, 2019
Jonah Gabry, Daniel Simpson, Aki Vehtari   +2 more
exaly  

Probabilistic framework to evaluate the resilience of engineering systems using Bayesian and dynamic Bayesian networks

Reliability Engineering and System Safety, 2020
Omar Kammouh, Paolo Gardoni, Gian Paolo Cimellaro   +2 more
exaly