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libDAI: A Free and Open Source C++ Library for Discrete Approximate Inference in Graphical Models

2010

Article

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This paper describes the software package libDAI, a free & open source C++ library that provides implementations of various exact and approximate inference methods for graphical models with discrete-valued variables. libDAI supports directed graphical models (Bayesian networks) as well as undirected ones (Markov random fields and factor graphs). It offers various approximations of the partition sum, marginal probability distributions and maximum probability states. Parameter learning is also supported. A feature comparison with other open source software packages for approximate inference is given. libDAI is licensed under the GPL v2+ license and is available at http://www.libdai.org.

Author(s): Mooij, JM.
Journal: Journal of Machine Learning Research
Volume: 11
Pages: 2169-2173
Year: 2010
Month: August
Day: 0

Department(s): Empirical Inference
Bibtex Type: Article (article)

Digital: 0
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

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BibTex

@article{6762,
  title = {libDAI: A Free and Open Source C++ Library for Discrete Approximate Inference in Graphical Models},
  author = {Mooij, JM.},
  journal = {Journal of Machine Learning Research},
  volume = {11},
  pages = {2169-2173},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  month = aug,
  year = {2010},
  month_numeric = {8}
}