Inference and Sampling#

Core Inference Classes#

Inference(model)

Base class for all inference algorithms.

VariableElimination(model)

BeliefPropagation(model)

Class for performing inference using Belief Propagation method.

BeliefPropagationWithMessagePassing(model[, ...])

Class for performing efficient inference using Belief Propagation method on factor graphs with no loops.

Mplp(model)

Class for performing approximate inference using Max-Product Linear Programming method.

DBNInference(model)

Class for performing inference using Belief Propagation method for the input Dynamic Bayesian Network.

Approximate Inference and Sampling#

ApproxInference(model)

Initializes the Approximate Inference class.

BayesianModelInference(model)

Class to calculate probability (pmf) values specific to Bayesian Models

BayesianModelSampling(model)

Class for sampling methods specific to Bayesian Models

GibbsSampling([model])

Class for performing Gibbs sampling.

Elimination-Order Heuristics#

BaseEliminationOrder(model)

Init method for the base class of Elimination Orders.

WeightedMinFill(model)

MinNeighbors(model)

MinWeight(model)

MinFill(model)