libDAI
File List
Here is a list of all documented files with brief descriptions:
[detail level 1234]
o-include
|\-dai
| o-matlab
| |\*matlab.hDefines some utility functions for interfacing with MatLab
| o*alldai.hMain libDAI header file. It #includes all other libDAI headers
| o*bbp.hDefines class BBP, which implements Back-Belief-Propagation
| o*bipgraph.hDefines the BipartiteGraph class, which represents a bipartite graph
| o*bp.hDefines class BP, which implements (Loopy) Belief Propagation
| o*bp_dual.hDefines class BP_dual, which is used primarily by BBP
| o*cbp.hDefines class CBP, which implements Conditioned Belief Propagation
| o*clustergraph.hDefines class ClusterGraph, which is used by JTree, TreeEP and HAK
| o*createfg.hProvides functionality for input/output of data structures in various file formats
| o*dag.hDefines the DAG class, which represents a directed acyclic graph
| o*daialg.hDefines the general interface for inference methods in libDAI (classes InfAlg, DaiAlg<>, DaiAlgFG and DaiAlgRG)
| o*decmap.hDefines class DecMAP, which constructs a MAP state by decimation
| o*doc.hContains additional doxygen documentation
| o*emalg.hDefines classes related to Expectation Maximization (EMAlg, ParameterEstimation, CondProbEstimation and SharedParameters)
| o*enum.hDefines the DAI_ENUM macro, which can be used to define an enum with additional functionality
| o*evidence.hDefines class Evidence, which stores multiple observations of joint states of variables
| o*exactinf.hDefines ExactInf class, which can be used for exact inference on small factor graphs
| o*exceptions.hDefines the Exception class and macros for throwing exceptions and doing assertions
| o*factor.hDefines TFactor<> and Factor classes which represent factors in probability distributions
| o*factorgraph.hDefines the FactorGraph class, which represents factor graphs (e.g., Bayesian networks or Markov random fields)
| o*factorsp.hDefines TFactorSp<> class which represents sparse factors in probability distributions
| o*fbp.hDefines class FBP, which implements Fractional Belief Propagation
| o*fo.hDefines various function objects
| o*gibbs.hDefines class Gibbs, which implements Gibbs sampling
| o*graph.hDefines the GraphAL class, which represents an undirected graph as an adjacency list
| o*hak.hDefines class HAK, which implements a variant of Generalized Belief Propagation
| o*index.hDefines the IndexFor, multifor, Permute and State classes, which all deal with indexing multi-dimensional arrays
| o*io.hProvides functionality for input/output of data structures in various file formats
| o*jtree.hDefines class JTree, which implements the junction tree algorithm
| o*lc.hDefines class LC, which implements loop corrections for approximate inference
| o*mf.hDefines class MF which implements the Mean Field algorithm
| o*mr.hDefines class MR, which implements loop corrections as proposed by Montanari and Rizzo
| o*prob.hDefines TProb<> and Prob classes which represent (probability) vectors (e.g., probability distributions of discrete random variables)
| o*probsp.hDefines TProbSp<> class which represents sparse (probability) vectors
| o*properties.hDefines the Property and PropertySet classes, which are mainly used for managing parameters of inference algorithms
| o*regiongraph.hDefines classes Region, FRegion and RegionGraph, which implement a particular subclass of region graphs
| o*smallset.hDefines the SmallSet<> class, which represents a set (optimized for a small number of elements)
| o*spvector.hDefines spvector<> class, which implements a sparse vector (using a std::vector)
| o*spvector_map.hDefines spvector_map<> class, which implements a sparse vector (using a std::map)
| o*treeep.hDefines class TreeEP, which implements Tree Expectation Propagation
| o*trwbp.hDefines class TRWBP, which implements Tree-Reweighted Belief Propagation
| o*util.hDefines general utility functions and adds an abstraction layer for platform-dependent functionality
| o*var.hDefines class Var, which represents a discrete random variable
| o*varset.hDefines the VarSet class, which represents a set of random variables
| \*weightedgraph.hDefines some utility functions for (weighted) undirected graphs, trees and rooted trees
\*config.h