 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 |
   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 |
   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) |
   factorsp.h | Defines TFactorSp<> class which represents sparse factors in probability distributions |
   fbp.h | Defines class FBP, which implements Fractional Belief Propagation |
   fo.h | Defines various function objects |
   gibbs.h | Defines class Gibbs, which implements Gibbs sampling |
   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) |
   probsp.h | Defines TProbSp<> class which represents sparse (probability) vectors |
   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) |
   spvector.h | Defines spvector<> class, which implements a sparse vector (using a std::vector) |
   spvector_map.h | Defines spvector_map<> class, which implements a sparse vector (using a std::map) |
   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 | |