We provide a survey of non-stationary surrogate models which utilize Gaussian processes (GPs) or variations thereof, including non-stationary 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（GP）或其变体的非平稳代理模型，包括非平稳核自适应、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。我们还概述了公开可用的软件实现，并在一个涉及8维卫星阻力计算机实验的对比评估中作出总结。该示例的代码已公开于Git仓库。