Learning elliptic partial differential equations with randomized linear algebra
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Publication:2697403
DOI10.1007/s10208-022-09556-wOpenAlexW3127355902WikidataQ114228261 ScholiaQ114228261MaRDI QIDQ2697403
Publication date: 12 April 2023
Published in: Foundations of Computational Mathematics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2102.00491
Green's functionHilbert-Schmidt operatorslow-rank approximationrandomized SVDdata-driven discovery of PDEs
Gaussian processes (60G15) Inverse problems for PDEs (35R30) Green's functions for elliptic equations (35J08) Fundamental solutions, Green's function methods, etc. for boundary value problems involving PDEs (65N80) Numerical methods for low-rank matrix approximation; matrix compression (65F55)
Related Items (2)
Convergence Rates for Learning Linear Operators from Noisy Data ⋮ Sparse Recovery of Elliptic Solvers from Matrix-Vector Products
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