Probabilistic learning on manifolds constrained by nonlinear partial differential equations for small datasets

DOI10.1016/j.cma.2021.113777zbMath1506.65175arXiv2010.14324OpenAlexW3097302541WikidataQ115358875 ScholiaQ115358875MaRDI QIDQ2236928

Christian Soize, Roger G. Ghanem

Publication date: 26 October 2021

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2010.14324

zbMATH Keywords

partial differential equationsprobabilistic learningmachine learninguncertainty quantificationsmall datasetPLoM

Mathematics Subject Classification ID

Statistics on manifolds (62R30) General second-order stochastic processes (60G12) PDEs with randomness, stochastic partial differential equations (35R60) Probabilistic methods, particle methods, etc. for initial value and initial-boundary value problems involving PDEs (65M75)

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Uses Software

• EGO
• PMTK
• DGM

Cites Work

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