Web: http://arxiv.org/abs/2201.08530

Jan. 24, 2022, 2:10 a.m. | Tal Shnitzer, Hau-Tieng Wu, Ronen Talmon

cs.LG updates on arXiv.org arxiv.org

Multivariate time-series have become abundant in recent years, as many
data-acquisition systems record information through multiple sensors
simultaneously. In this paper, we assume the variables pertain to some geometry
and present an operator-based approach for spatiotemporal analysis. Our
approach combines three components that are often considered separately: (i)
manifold learning for building operators representing the geometry of the
variables, (ii) Riemannian geometry of symmetric positive-definite matrices for
multiscale composition of operators corresponding to different time samples,
and (iii) spectral analysis …

analysis arxiv ml

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