High-dimensional intrinsic interpolation using Gaussian process regression and diffusion maps

DOI10.1007/s11004-017-9705-yzbMath1406.86047OpenAlexW2763008025MaRDI QIDQ1719851

Joshua A. White, Roger G. Ghanem, Charanraj A. Thimmisetty, Xiao Chen

Publication date: 12 February 2019

Published in: Mathematical Geosciences (Search for Journal in Brave)

Full work available at URL: https://www.osti.gov/biblio/1400095

zbMATH Keywords

KrigingGaussian process regressionintrinsic metricsdiffusion distanceinterpolation on manifoldintrinsic interpolation

Mathematics Subject Classification ID

Inverse problems in geophysics (86A22) Geological problems (86A60)

Related Items (1)

Diffusion maps-aided neural networks for the solution of parametrized PDEs

Cites Work

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• Data-driven probability concentration and sampling on manifold
• Spatial variation. 2nd ed
• Diffusion maps
• Numerical Methods for Large Eigenvalue Problems
• Bayesian Prediction of Transformed Gaussian Random Fields
• Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps
• The origins of kriging

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