## ProGraM: Probabilistic Graphical Models Research Group and Lab

The mission of the ProGraM Lab is the theory and application of Probabilistic Graphical Models (PGM).

The members of ProGraM are involved in the following research topics

- Foundations of Bayesian Networks (BN), Dynamic Bayesian Networks (DBN) and Decision Networks (DN): Influence Diagrams (ID) and LIMIDs;
- Foundations and inference methods for Continuous Time Bayesian Networks (CTBN); in particular, inside the ProGraM Lab has been developed the formalism of Generalized Continuous Time Bayesian Networks (GCTBN)
- Applications of directed PGMs to dependability and reliability; (BN, DBN, GCTBN, DN)
- Applications of DN to cyber-security
- Integration of undirected models, in particular Markov Random Fields (MRF) with Case-Based Reasoning (CBR)
- Data mining with PGMs

ProGraM is the home lab of the **RADyBaN** tool (**R**eliability **A**nalysis with **Dy**namic **Ba**yesian **N**etworks)