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DOE OSTI · 2447287

Kernelized approaches to streaming compression of scientific data

Russo, Benjamin P.·Archibald, Richard
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Abstract

In this paper three algorithms are developed for the streaming compression of scientific data. The algorithms presented are reliant on the theory of vector-valued reproducing kernel Hilbert spaces and operator valued kernel. Further, the scientific data is modeled as a snapshot of time dependent vector field F(x, t) over a manifold M and the recovery of the data is framed as a learning problem. These processes are then appropriately modified and ana lyzed for the streaming scenario in which data is generated without the ability to revisit past entries.

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97 MATHEMATICS AND COMPUTINGonline compressionstreaming datavector valued reproducing kernel Hilbert spaces

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BibTeXRIS

Russo, Benjamin P., Archibald, Richard. 2024-09-01. Kernelized approaches to streaming compression of scientific data. https://doi.org/10.3934/ammc.2024017

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