Accelerating algebraic multigrid methods via artificial neural networks
DOI10.1007/s10013-022-00597-wOpenAlexW3209079568MaRDI QIDQ2679755
Luca Dedè, Matteo Caldana, Paola Francesca Antonietti
Publication date: 23 January 2023
Published in: Vietnam Journal of Mathematics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2111.01629
finite element methodStokes problemelliptic PDEsconvolutional neural networksdeep learningalgebraic multigrid (AMG)
Multigrid methods; domain decomposition for boundary value problems involving PDEs (65N55) Artificial neural networks and deep learning (68T07) Stokes and related (Oseen, etc.) flows (76D07) Stability and convergence of numerical methods for boundary value problems involving PDEs (65N12) Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs (65N30) General topics in artificial intelligence (68T01) Numerical solution of discretized equations for boundary value problems involving PDEs (65N22)
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