Random Field Interpolation

Random Field Interpolation is a statistical estimation technique that, as a subclass of spatial interpolation methods, uniquely characterizes the prediction of unobserved values of a random field at unsampled locations based on the spatial correlation structure of the observed data.

14

Publications

1.7K

Citations

46

Authors

24

Institutions

Publications per year

2017–2026

4

Authors

46

  1. IH
    Ian H. Sloan

    UNSW Sydney, Australia

    2 publications · 47 citations

    2

    h-index

  2. FY
    Frances Y. Kuo

    UNSW Sydney, Australia

    2 publications · 47 citations

    2

    h-index

  3. HG
    Hermann G. Matthies

    Technische Universität Braunschweig, Germany

    1 publications · 22 citations

    1

    h-index

  4. SD
    Sergey Dolgov

    University of Bath, United Kingdom

    1 publications · 22 citations

    1

    h-index

  5. BN
    Boris N. Khoromskij

    Max Planck Institute for Mathematics in the Sciences, Germany

    1 publications · 22 citations

    1

    h-index

1–5 of 46

Venues

  1. Infoscience (Ecole Polytechnique Fédérale de Lausanne)

    Repository · 1 publications · 15 citations

    1

    h-index

  2. The Annals of Probability

    1 publications · 49 citations

    1

    h-index

  3. SIAM/ASA Journal on Uncertainty Quantification

    JUQ · 1 publications · 18 citations

    1

    h-index

  4. 1

    h-index

  5. arXiv (Cornell University)

    Repository · 1 publications · 22 citations

    1

    h-index

1–5