We provide a survey of nonstationary surrogate models which utilize Gaussian processes (GPs) or variations thereof, including nonstationary kernel adaptations, partition and local GPs, and spatial warpings through deep Gaussian processes. We also overview publicly available software implementations and conclude with a bake-off involving an 8-dimensional satellite drag computer experiment. Code for this example is provided in a public git repository.

翻译：本文综述了利用高斯过程（GPs）及其变体的非平稳代理模型，包括非平稳核函数适配、分区与局部高斯过程，以及通过深度高斯过程实现的空间扭曲方法。我们还概述了公开可用的软件实现，并以一个8维卫星阻力计算机实验的对比测试作为总结。该示例的代码已发布于公共git仓库。