Paper Info
Title
OpenGM: A C++ Library for Discrete Graphical Models
Abstract
OpenGM is a C++ template library for defining discrete graphical models and performing inference on these models, using a wide range of state-of-the-art algorithms. No restrictions are imposed on the factor graph to allow for higher-order factors and arbitrary neighborhood structures. Large models with repetitive structure are handled efficiently because (i) functions that occur repeatedly need to be stored only once, and (ii) distinct functions can be implemented differently, using different encodings alongside each other in the same model. Several parametric functions (e.g. metrics), sparse and dense value tables are provided and so is an interface for custom C++ code. Algorithms are separated by design from the representation of graphical models and are easily exchangeable. OpenGM, its algorithms, HDF5 file format and command line tools are modular and extendible.
Year
Venue
Keywords
2012
CoRR
machine learning,computer science,artificial intelligence,statistics
Field
DocType
Volume
Factor graph,File format,Hierarchical Data Format,Parametric equation,Computer science,Theoretical computer science,C mathematical functions,Mathematical software,Artificial intelligence,Modular design,Graphical model,Machine learning
Journal
abs/1206.0111
Citations 
PageRank 
References 
37
1.41
11
Authors
3
Name
Order
Citations
PageRank
Björn Andres122012.72
Thorsten Beier2695.79
Jörg H. Kappes320212.16