PRAiSE (for Probabilistic Reasoning As Symbolic Evaluation) is a library developed at SRI International's Artificial Intelligence Center, which implements the ideas presented in the following paper:

"Probabilistic Inference Modulo Theories",
de Salvo Braz, R., O'Reilly, C., Gogate, V., Dechter, R.,
Proc. of the 25th International Joint Conference on Artificial Intelligence (IJCAI-16).
(revised version, original version, bibtex)

The current library and demo (below) is capable of performing probabilistic inference on models defined with: In the future, we will also have: The underlying technology used to support these capabilities is provided by the AIC-Expresso Library.

Your possible next steps:

PRAiSE Demo App (requires a browser supporting Java Web Start. You also need to whitelist http://aic-sri-international.github.io and authorize applications to run from the browser in the Java Control Panel, which in Windows is an icon in the Control Panel, and in other platforms is a separate application).

Screenshot of PRAiSE demo