Surrogates Gaussian Process Modeling Design And Optimization For The Appli - Robert B. Gramacy

Surrogates: A Graduate Textbook, Or Professional Handbook, On Topics At The Interface Between Machine Learning, Spatial Statistics, Computer Simulation, Meta-modeling (i.e., Emulation), Design Of Experiments, And Optimization. Experimentation Through Simulation, Human Out-of-the-loop Statistical Support (focusing On The Science), Management Of Dynamic Processes, Online And Real-time Analysis, Automation, And Practical Application Are At The Forefront. Topics Include:gaussian Process (gp) Regression For Flexible Nonparametric And Nonlinear Modeling.applications To Uncertainty Quantification, Sensitivity Analysis, Calibration Of Computer Models To Field Data, Sequential Designactive Learning And (blackboxbayesian) Optimization Under Uncertainty.