inference Directory Reference

Directory dependency graph for inference:

Directories
	tools

Files
	GibbsSampling.cpp
	GibbsSampling.h
	This file contains Gibbs sampling class definition.
	GibbsSampling_tpl.h
	Implementation of Gibbs Sampling for inference in Bayesian networks.
	importanceSampling.cpp
	importanceSampling.h
	This file contains Importance sampling class definition.
	importanceSampling_tpl.h
	Implementation of Importance Sampling for inference in Bayesian networks.
	lazyPropagation.cpp
	lazyPropagation.h
	Implementation of a Shafer-Shenoy's-like version of lazy propagation for inference in Bayesian networks.
	lazyPropagation_tpl.h
	Implementation of lazy propagation for inference in Bayesian networks.
	loopyBeliefPropagation.cpp
	loopyBeliefPropagation.h
	This file contains gibbs sampling (for BNs) class definitions.
	loopyBeliefPropagation_tpl.h
	Implementation of Loopy Belief Propagation in Bayesian networks.
	loopySamplingInference.cpp
	loopySamplingInference.h
	This file implements a Hybrid sampling class using LoopyBeliefPropagation and an approximate Inference method.
	loopySamplingInference_tpl.h
	Implements approximate inference algorithms from Loopy Belief Propagation.
	MonteCarloSampling.cpp
	MonteCarloSampling.h
	This file contains Monte Carlo sampling class definition.
	MonteCarloSampling_tpl.h
	Implementation of Monte Carlo Sampling for inference in Bayesian Networks.
	ShaferShenoyInference.cpp
	ShaferShenoyInference.h
	Implementation of Shafer-Shenoy's algorithm for inference in Bayesian networks.
	ShaferShenoyInference_tpl.h
	Implementation of Shafer-Shenoy's propagation for inference in Bayesian networks.
	variableElimination.cpp
	variableElimination.h
	Implementation of a variable elimination algorithm for inference in Bayesian networks.
	variableElimination_tpl.h
	Implementation of Variable Elimination for inference in Bayesian networks.
	weightedSampling.cpp
	weightedSampling.h
	This file contains Weighted sampling class definition.
	weightedSampling_tpl.h
	Implementation of Weighted Sampling for inference in Bayesian networks.