A decision-making machine learning approach in Hermite spectral approximations of partial differential equations

DOI10.1007/s10915-022-01853-4zbMath1490.65297arXiv2104.02181OpenAlexW3147774872WikidataQ114225565 ScholiaQ114225565MaRDI QIDQ2149019

Daniele Funaro, Lorella Fatone, Gianmarco Manzini

Publication date: 24 June 2022

Published in: Journal of Scientific Computing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2104.02181

zbMATH Keywords

neural networksmachine learningspectral methodssupport vector machinegeneralized Hermite functionstime-dependent heat equation

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Spectral, collocation and related methods for boundary value problems involving PDEs (65N35) Vlasov equations (35Q83)

Related Items (1)

Physics-based adaptivity of a spectral method for the Vlasov-Poisson equations based on the asymmetrically-weighted Hermite expansion in velocity space

Uses Software

• KELLEY
• LIBSVM
• SpectralPlasmaSolver
• DGM
• NSFnets
• hp-VPINNs

Cites Work

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