Computationally efficient approximation of large-scale and high-dimensional simulations
Simulations are used by scientists and engineers to study complex real systems such as material micro-structure or passenger flows through a new airport design. Frequently, these complex simulations are too expensive to allow full exploration of the unknown relationship, much less optimization. A common solution is to build a computationally efficient approximate simulation, or emulator. Here, we discuss several aspects of building an accurate and efficient emulator in the context of large-scale and high-dimensional simulations. Specifically, we examine sources of inaccuracy related to data collection and present two techniques well-adapted to large-scale and high-dimensional simulations, local Gaussian process fitting and multi-resolution functional ANOVA modeling.