Gaussian Process Regression for Surface Interpolation
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore Gaussian Process Regression (GPR) for surface interpolation in this 48-minute tutorial presented by Zhiqiao Dong and Manan Mehta from the University of Illinois Urbana-Champaign. Learn about the fundamentals of GPR and its applications in manufacturing for generating high-resolution surface estimations from coarser measurement data. Discover a new technique called filtered kriging (FK) that improves interpolation performance using a pre-filter. Follow along with a hands-on demonstration of the Filtered Kriging Lab tool and understand its application to periodic surfaces manufactured by two-photon lithography. Gain insights into spatial interpolation, covariance modeling, and the GPR workflow through practical examples and in-depth explanations. Access additional resources, including the Filtered Kriging Lab tool and related downloads, to further enhance your understanding of this powerful nonparametric regression method.