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 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