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Kent is a generic report server that provides reports to users via a JSP/Servlet based interface. Internally report output is XML, which is transformed to HTML or any other supported format, as selected by the user.
Mocapy++ is a Dynamic Bayesian Network toolkit, implemented in C++. It supports discrete, multinomial, Gaussian, Kent, Von Mises and Poisson nodes. Inference and learning is done by Gibbs sampling/Stochastic-EM.