▼ include | |
▼ dai | |
▼ matlab | |
matlab.h | Defines some utility functions for interfacing with MatLab |
alldai.h | Main libDAI header file. It #includes all other libDAI headers |
bbp.h | Defines class BBP, which implements Back-Belief-Propagation |
bipgraph.h | Defines the BipartiteGraph class, which represents a bipartite graph |
bp.h | Defines class BP, which implements (Loopy) Belief Propagation |
bp_dual.h | Defines class BP_dual, which is used primarily by BBP |
cbp.h | Defines class CBP, which implements Conditioned Belief Propagation |
clustergraph.h | Defines class ClusterGraph, which is used by JTree, TreeEP and HAK |
cobwebgraph.h | Defines class CobwebGraph, which implements a type of region graph used by GLC |
createfg.h | Provides functionality for input/output of data structures in various file formats |
dag.h | Defines the DAG class, which represents a directed acyclic graph |
dai_config.h | Allows the user to specify which algorithms will be built into libDAI |
daialg.h | Defines the general interface for inference methods in libDAI (classes InfAlg, DaiAlg<>, DaiAlgFG and DaiAlgRG) |
decmap.h | Defines class DecMAP, which constructs a MAP state by decimation |
doc.h | Contains additional doxygen documentation |
emalg.h | Defines classes related to Expectation Maximization (EMAlg, ParameterEstimation, CondProbEstimation and SharedParameters) |
enum.h | Defines the DAI_ENUM macro, which can be used to define an enum with additional functionality |
evidence.h | Defines class Evidence, which stores multiple observations of joint states of variables |
exactinf.h | Defines ExactInf class, which can be used for exact inference on small factor graphs |
exceptions.h | Defines the Exception class and macros for throwing exceptions and doing assertions |
factor.h | Defines TFactor<> and Factor classes which represent factors in probability distributions |
factorgraph.h | Defines the FactorGraph class, which represents factor graphs (e.g., Bayesian networks or Markov random fields) |
fbp.h | Defines class FBP, which implements Fractional Belief Propagation |
gibbs.h | Defines class Gibbs, which implements Gibbs sampling |
glc.h | Defines classes GLC and Cobweb, which implement the "Generalized Loop Correction method" |
graph.h | Defines the GraphAL class, which represents an undirected graph as an adjacency list |
hak.h | Defines class HAK, which implements a variant of Generalized Belief Propagation |
index.h | Defines the IndexFor, multifor, Permute and State classes, which all deal with indexing multi-dimensional arrays |
io.h | Provides functionality for input/output of data structures in various file formats |
jtree.h | Defines class JTree, which implements the junction tree algorithm |
lc.h | Defines class LC, which implements loop corrections for approximate inference |
mf.h | Defines class MF which implements the Mean Field algorithm |
mr.h | Defines class MR, which implements loop corrections as proposed by Montanari and Rizzo |
prob.h | Defines TProb<> and Prob classes which represent (probability) vectors (e.g., probability distributions of discrete random variables) |
properties.h | Defines the Property and PropertySet classes, which are mainly used for managing parameters of inference algorithms |
regiongraph.h | Defines classes Region, FRegion and RegionGraph, which implement a particular subclass of region graphs |
smallset.h | Defines the SmallSet<> class, which represents a set (optimized for a small number of elements) |
treeep.h | Defines class TreeEP, which implements Tree Expectation Propagation |
trwbp.h | Defines class TRWBP, which implements Tree-Reweighted Belief Propagation |
util.h | Defines general utility functions and adds an abstraction layer for platform-dependent functionality |
var.h | Defines class Var, which represents a discrete random variable |
varset.h | Defines the VarSet class, which represents a set of random variables |
weightedgraph.h | Defines some utility functions for (weighted) undirected graphs, trees and rooted trees |
config.h | |