Bayes Blocks: An Implementation of the Variational Bayesian Building Blocks Framework
Markus Harva, Tapani Raiko, Antti Honkela, Harri Valpola and Juha Karhunen
In: 21st Conference on Uncertainty in Artificial Intelligence, UAI 2005, 26-29 Jul, 2005, Edinburgh, Scotland.
A software library for constructing and learning probabilistic models
is presented. The library offers a set of building blocks from
which a large variety of static and dynamic models can be built.
These include hierarchical models
for variances of other variables and many nonlinear models.
The underlying variational
Bayesian machinery, providing for fast and robust estimation but being
mathematically rather involved, is almost completely
hidden from the user thus making it very easy to use the library.
The building blocks include Gaussian, rectified Gaussian and
mixture-of-Gaussians variables and computational nodes which can be
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