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A software library for constructing and learning probabilistic models ispresented. The library offers a set of building blocks from which a largevariety of static and dynamic models can be built. These include hierarchicalmodels for variances of other variables and many nonlinear models. Theunderlying variational Bayesian machinery, providing for fast and robustestimation but being mathematically rather involved, is almost completelyhidden from the user thus making it very easy to use the library. The buildingblocks include Gaussian, rectified Gaussian and mixture-of-Gaussians variablesand computational nodes which can be combined rather freely.

Bayes Blocks: An Implementation of the Variational Bayesian Building Blocks Framework