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Framework for Gibbs sampling of probabilistic models

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Octocat-spinner-32 BayesStack
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Octocat-spinner-32 bayes-stack.cabal
README.mkd

bayes-stack: Parallel MCMC inference on graphical models

Bayes-stack is a framework for parallel probabilistic inference on graphical models. The framework provides infrastructure for easily implementing MCMC/Gibbs sampling methods capable of scaling to dozens of cores.

Along with the framework itself, several models using blocked Gibbs sampling are provided in network-topic-models/.

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