Gaussian process regression (GPR) is a nonparametric regression method with widespread applications in various scientific and engineering fields. In manufacturing, it has been used for surface interpolation that generates high-resolution surface estimations from coarser measurement data. This tutorial introduces you to a GPR-based technique called filtered kriging (FK), which uses a pre-filter to further improve interpolation performance, illustrated using periodic surfaces manufactured by two photon lithography. A simple example of Gaussian process is also included.

Researchers should cite this work as follows:

• Zhiqiao Dong, Manan Mehta (2022), "Filtered Kriging Lab," https://nanohub.org/resources/fkriging. (DOI: 10.21981/NAR4-DW39).

  BibTex | EndNote

1. Gaussian Processes
2. Gaussian process regression
3. Gaussian process regression (GPR)
4. interpolation
5. surface interpolation
6. two-photon lithography