Composite grid designs for adaptive computer experiments with fast inference
本文提出复合网格实验设计及序贯构建方法，用于精确模拟确定性计算机代码，并开发了能在大样本下快速进行高斯过程推断的计算方法，相比现有近似方法精度提升数个数量级。
Summary Experiments are often used to produce emulators of deterministic computer code. This article introduces composite grid experimental designs and a sequential method for building the designs for accurate emulation. Computational methods are developed that enable fast and exact Gaussian process inference even with large sample sizes. We demonstrate that the proposed approach can produce emulators that are orders of magnitude more accurate than current approximations at a comparable computational cost.