Infer.NET supports expectation propagation (including belief propagation as a special case), variational message passing (also known as variational Bayes), max product (for discrete models), and block Gibbs sampling.

You can use Infer.NET to solve many different kinds of machine learning problems, from standard problems like classification, recommendation or clustering through to customised solutions to domain-specific problems.

Can be used on Windows (.NET), OSX or Linux (using mono)