Online approximations for wind-field models


We study online approximations to Gaussian process models for spatially distributed systems. We apply our method to the prediction of wind fields over the ocean surface from scatterometer data. Our approach combines a sequential update of a Gaussian approximation to the posterior with a sparse representation that allows to treat problems with a large number of observations.

Publication DOI:
Divisions: ?? 50811700Jl ??
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
Additional Information: The original publication is available at
Event Title: International Conference on Neural Networks
Event Type: Other
Event Dates: 2001-01-01 - 2001-01-01
Uncontrolled Keywords: online approximations,Gaussian process models,spatially distributed systems,scatterometer data,Gaussian approximation
ISBN: 9783540424864
Last Modified: 26 Feb 2024 08:06
Date Deposited: 14 Sep 2009 13:21
Full Text Link:
Related URLs: http://www.spri ... pa865c0q4k55wt/ (Publisher URL)
PURE Output Type: Chapter
Published Date: 2001-01-01
Authors: Csató, Lehel
Cornford, Dan (ORCID Profile 0000-0001-8787-6758)
Opper, Manfred



Version: Accepted Version

Export / Share Citation


Additional statistics for this record