Advances in Probabilistic Reasoning
  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.
