Physics Information Aided Kriging using Stochastic Simulation Models
Xiu Yang, G. Tartakovsky, Alexandre M. Tartakovsky
Abstract
Related DatabasesWeb of Science You must be logged in with an active subscription to view this.Article DataHistorySubmitted: 14 April 2020Accepted: 28 June 2021Published online: 15 November 2021Keywordsphysics information, Gaussian process regression, active learning, error boundAMS Subject Headings65C60, 42C05, 41A10Publication DataISSN (print): 1064-8275ISSN (online): 1095-7197Publisher: Society for Industrial and Applied MathematicsCODEN: sjoce3
Topics & Concepts
KrigingGaussian processRegressionApplied mathematicsGaussianMathematicsComputer scienceRegression analysisStatisticsIndustrial engineeringStatistical physicsEngineeringPhysicsQuantum mechanicsAdvanced Multi-Objective Optimization AlgorithmsProbabilistic and Robust Engineering DesignGaussian Processes and Bayesian Inference