Abstract
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.
Cite
CITATION STYLE
Csató, L., Cornford, D., & Opper, M. (2001). Online approximations for wind-field models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2130, pp. 300–307). Springer Verlag. https://doi.org/10.1007/3-540-44668-0_43
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