Active Learning-based Domain Adaptive Localized Polynomial Chaos Expansion

Abstract

Effective construction of a general purpose surrogate model based on polynomial chaos expansion.• Novel method for sequential decomposition of the input random space and construction of local approximations.• Sequential domain decomposition and sample size extension based on an active learning methodology.• Active learning is represented by variance-based Θ criterion developed for polynomial chaos expansion.