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aGrUM
0.20.3
a C++ library for (probabilistic) graphical models
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Copyright (c) 2005-2021 by Pierre-Henri WUILLEMIN() & Christophe GONZALES() info_at_agrum_dot_org. More...
#include <agrum/BN/inference/GibbsSampling.h>
#include <agrum/BN/inference/MonteCarloSampling.h>
#include <agrum/BN/inference/importanceSampling.h>
#include <agrum/BN/inference/tools/approximateInference.h>
#include <agrum/BN/inference/tools/marginalTargetedInference.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 | |
gum | |
Copyright (c) 2005-2021 by Pierre-Henri WUILLEMIN() & Christophe GONZALES() info_at_agrum_dot_org. | |
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 > |
Copyright (c) 2005-2021 by Pierre-Henri WUILLEMIN() & Christophe GONZALES() info_at_agrum_dot_org.
This library is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public License along with this library. If not, see http://www.gnu.org/licenses/.
This file implements a Hybrid sampling class using LoopyBeliefPropagation and an approximate Inference method.
Definition in file loopySamplingInference.h.