Exploiting local and repeated structure in dynamic Bayesian networks

Abstract

© 2015 Elsevier B.V. All rights reserved. We introduce the structural interface algorithm for exact probabilistic inference in Dynamic Bayesian Networks. It unifies state-of-the-art techniques for inference in static and dynamic networks, by combining principles of knowledge compilation with the interface algorithm. The resulting algorithm not only exploits the repeated structure in the network, but also the local structure, including determinism, parameter equality and context-specific independence. Empirically, we show that the structural interface algorithm speeds up inference in the presence of local structure, and scales to larger and more complex networks.publisher: Elsevier articletitle: Exploiting local and repeated structure in Dynamic Bayesian Networks journaltitle: Artificial Intelligence articlelink: http://dx.doi.org/10.1016/j.artint.2015.12.001 content_type: article copyright: Copyright © 2015 Elsevier B.V. All rights reserved.status: publishe