Advances in Probabilistic Reasoning - Geiger, Dan; Heckerman, David (Proceedings of the Seventh Conference on Uncertainty in Artificial Intelligence, 1991)
This paper discuses multiple Bayesian networks representation paradigms for encoding asymmetric independence assertions. We offer three contributions: (1) an inference mechanism that makes explicit use of asymmetric independence to speed up computations, (2) a simplified definition of similarity networks and extensions of their theory, and (3) a generalized representation scheme that encodes more types of asymmetric independence assertions than do similarity networks.