Compressed Principal Component Analysis of Non-Gaussian Vectors
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Publication:5139351
DOI10.1137/20M1322029zbMath1451.62069MaRDI QIDQ5139351
Christian Soize, Marc P. Mignolet
Publication date: 8 December 2020
Published in: SIAM/ASA Journal on Uncertainty Quantification (Search for Journal in Brave)
inverse problemstochastic modelingprincipal component analysisstochastic processessymmetric polynomialsrandom fieldsreduction methodstochastic modeluncertainty quantificationrandom eigenvectorsnon-Gaussian vectorcompressed principal component analysis
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Probabilistic learning inference of boundary value problem with uncertainties based on Kullback-Leibler divergence under implicit constraints ⋮ Polynomial-chaos-based conditional statistics for probabilistic learning with heterogeneous data applied to atomic collisions of helium on graphite substrate
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