Inference in hybrid Bayesian networks with Mixtures of Truncated Basis Functions

TLDR: A structure for handling probability potentials called Sum-Product factorized potentials, and it is shown how these potentials facilitate ecient inference based on properties of the MoTBFs and ideas similar to the ones underlying Lazy propagation (postponing operations and keeping factorized representations of the potentials).

Abstract: In this paper we study the problem of exact inference in hybrid Bayesian networks using mixtures of truncated basis functions (MoTBFs). We propose a structure for handling probability potentials called Sum-Product factorized potentials, and show how these potentials facilitate ecient inference based on i) properties of the MoTBFs and ii) ideas similar to the ones underlying Lazy propagation (postponing operations and keeping factorized representations of the potentials). We report on preliminary experiments demonstrating the eciency of the proposed method in comparison with existing algorithms.