Compiling relational Bayesian networks for exact inference

We describe in this paper a system for exact inference with relational Bayesian networks as defined in the publicly available Primula tool. The system is based on compiling propositional instances of relational Bayesian networks into arithmetic circuits and then performing online inference by evaluating and differentiating these circuits in time linear in their size. We report on experimental results showing successful compilation and efficient inference on relational Bayesian networks, whose Primula

• Type: Journal
• Year: 2006
• Where: IJAR
• Authors: Mark Chavira, Adnan Darwiche, Manfred Jaeger
• Keywords: Exact Inference, IJAR 2006, Propositional Instances, Relational Bayesian Networks