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aGrUM 2.3.2
a C++ library for (probabilistic) graphical models
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This file implements a Hybrid sampling class using LoopyBeliefPropagation and an approximate Inference method. More...
#include <agrum/BN/inference/GibbsSampling.h>#include <agrum/BN/inference/importanceSampling.h>#include <agrum/BN/inference/MonteCarloSampling.h>#include <agrum/BN/inference/weightedSampling.h>#include <agrum/BN/inference/loopySamplingInference_tpl.h>Go to the source code of this file.
Classes | |
| class | gum::LoopySamplingInference< GUM_SCALAR, APPROX > |
| <agrum/BN/inference/loopySamplingInference.h> More... | |
Namespaces | |
| namespace | gum |
| gum is the global namespace for all aGrUM entities | |
Typedefs | |
| template<typename GUM_SCALAR> | |
| using | gum::HybridMonteCarloSampling = LoopySamplingInference< GUM_SCALAR, MonteCarloSampling > |
| template<typename GUM_SCALAR> | |
| using | gum::HybridWeightedSampling = LoopySamplingInference< GUM_SCALAR, WeightedSampling > |
| template<typename GUM_SCALAR> | |
| using | gum::HybridImportanceSampling = LoopySamplingInference< GUM_SCALAR, ImportanceSampling > |
| template<typename GUM_SCALAR> | |
| using | gum::HybridGibbsSampling = LoopySamplingInference< GUM_SCALAR, GibbsSampling > |
This file implements a Hybrid sampling class using LoopyBeliefPropagation and an approximate Inference method.
Definition in file loopySamplingInference.h.