Another Look at Neural Multigrid

DOI10.1142/S0129183197000187zbMath0945.65137arXivhep-lat/9610035OpenAlexW2137275888MaRDI QIDQ4488312

Martin Bäker

Publication date: 5 July 2000

Published in: International Journal of Modern Physics C (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/hep-lat/9610035

zbMATH Keywords

algorithmconjugate gradient methodgauge fieldsneural netinterpolation operatorsneural multigrid methodordered Laplace equation

Mathematics Subject Classification ID

Multigrid methods; domain decomposition for boundary value problems involving PDEs (65N55) Iterative numerical methods for linear systems (65F10) Quantum field theory on lattices (81T25) Laplace operator, Helmholtz equation (reduced wave equation), Poisson equation (35J05) Neural nets applied to problems in time-dependent statistical mechanics (82C32) Finite difference methods for boundary value problems involving PDEs (65N06)

Related Items (1)

Connections between numerical algorithms for PDEs and neural networks

Cites Work

• Analysis of a Multigrid Method as an Iterative Technique for Solving Linear Systems

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