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Bayesian Inference Under Probability Constraints
Anna Pernestål, Mattias Nyberg
151 - 156
Frontiers in Artificial Intelligence and Applications
Volume 173: Tenth Scandinavian Conference on Artificial Intelligence
Abstract

Inspired by the problem of fault isolation we consider Bayesian inference from training data and background knowledge. We discuss how the background knowledge can be translated to equality constraints and show how it is introduced in the computations. The main advantage of combining data and background knowledge is achieved when the amount of data is limited.

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