Exploiting Evidence in Probabilistic Inference

We define the notion of compiling a Bayesian network with evidence and provide a spe- cific approach for evidence-based compila- tion, which makes use of logical processing. The approach is practical and advantageous in a number of application areas—including maximum likelihood estimation, sensitivity analysis, and MAP computations—and we provide specific empirical results in the do- main of genetic linkage analysis. We also show that the approach is applicable for net- works that do not contain determinism, and show that it empirically subsumes the per- formance of the quickscore algorithm when applied to noisy-or networks.