Surrogate Model–Assisted Learning of Conditional Probability Tables of Bayesian Networks Describing Structural Systems

Abstract

AbstractBayesian network (BN) is an effective tool to describe and interpret the probability distribution of a complex phenomenon. Essential building blocks in discrete BNs are conditional probability tables (CPTs) quantifying statistical dependence ...