Polynomial Chaos Expanded Gaussian Process: A Transparent and Interpretable Approach for Modeling Complex Nonlinear Relationships

The Polynomial Chaos Expanded Gaussian Process (PCEGP) is a novel machine learning approach that leverages polynomial chaos expansion to calculate input-dependent hyperparameters of a Gaussian process, enabling effective modeling of both global and local behavior in complex processes.