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Bayesian inference using Gibbs sampling (BUGS) is a statistical software for performing Bayesian inference using Markov chain Monte Carlo (MCMC) methods. It was developed by David Spiegelhalter at the Medical Research Council Biostatistics Unit in Cambridge in 1989 and released as free software in 1991.
A Bayesian network (also known as a Bayes network, Bayes net, belief network, or decision network) is a probabilistic graphical model that represents a set of variables and their conditional dependencies via a directed acyclic graph (DAG). [1] While it is one of several forms of causal notation, causal networks are special cases of Bayesian ...
Bayesian optimization of a function (black) with Gaussian processes (purple). Three acquisition functions (blue) are shown at the bottom. [8]Bayesian optimization is typically used on problems of the form (), where is a set of points, , which rely upon less (or equal to) than 20 dimensions (,), and whose membership can easily be evaluated.
It can then be shown that the points of convergence of the sum-product algorithm represent the points where the free energy in such a system is minimized. Similarly, it can be shown that a fixed point of the iterative belief propagation algorithm in graphs with cycles is a stationary point of a free energy approximation.
Bayesian programming is a formalism and a methodology for having a technique to specify probabilistic models and solve problems when less than the necessary information is available.
bnt on GitHub: the Bayes Net Toolbox for Matlab, by Kevin Murphy, (released under a GPL license) Graphical Models Toolkit (GMTK): an open-source, publicly available toolkit for rapidly prototyping statistical models using dynamic graphical models (DGMs) and dynamic Bayesian networks (DBNs). GMTK can be used for applications and research in ...
CalculiX is a free and open-source finite-element analysis application that uses an input format similar to Abaqus. It has an implicit and explicit solver (CCX) written by Guido Dhondt and a pre- and post-processor (CGX) written by Klaus Wittig. [1] The original software was written for the Linux [2] operating system.
Bayes classifier; Bayes' theorem; Bayesian efficiency; Bayesian epistemology; Bayesian experimental design; Bayesian game; Bayesian history matching; Bayesian interpretation of kernel regularization; Bayesian model reduction; Bayesian programming; Bayesian regret; Bayesian structural time series; Bayesian survival analysis; Bayesian vector ...