Infer.NET is a framework for running Bayesian inference in graphical models. It can also be used for probabilistic programming.
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Pros
Pro Supports multiple inference algorithms
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.
Pro Versatile
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.
Pro Cross platform
Can be used on Windows (.NET), OSX or Linux (using mono)
Cons
Con No commercial license
Infer.NET is free for academic use. However, at this time, commercial use of Infer.NET is limited to Microsoft. No other commercial licenses are available.