Active emulation of computer codes with Gaussian processes – Application to remote sensing
作者：
Highlights：
• Introduction of methodology for active multi-output Gaussian process emulators.
• Gaussian processes allow the construction of accurate, compact and interpretable emulators.
• Adaptive sequential construction of both the emulator and look-up-table.
• New acquisition function combines function geometry and predictive uncertainty.
• Application to complex codes used on remote sensing leads to considerable computational savings.
摘要
•Introduction of methodology for active multi-output Gaussian process emulators.•Gaussian processes allow the construction of accurate, compact and interpretable emulators.•Adaptive sequential construction of both the emulator and look-up-table.•New acquisition function combines function geometry and predictive uncertainty.•Application to complex codes used on remote sensing leads to considerable computational savings.
论文关键词：Active learning,Gaussian process,Emulation,Design of experiments,Computer code,Remote sensing,Radiative transfer model
论文评审过程：Received 18 February 2019, Revised 25 October 2019, Accepted 3 November 2019, Available online 13 November 2019, Version of Record 2 December 2019.
论文官网地址：https://doi.org/10.1016/j.patcog.2019.107103
