Výsledky vyhledávání - "Computational methods for problems pertaining to operator theory"

Render unto Numerics: Orthogonal Polynomial Neural Operator for PDEs with Nonperiodic Boundary Conditions: Render unto numerics: orthogonal polynomial neural operator for PDEs with nonperiodic boundary conditions

Autoři: Ziyuan Liu Haifeng Wang Hong Zhang a další

Zdroj: SIAM Journal on Scientific Computing. 46:C323-C348

Témata: scientific machine learning, deep learning-based PDE solver, Computational methods for problems pertaining to operator theory, Computational learning theory, spectral method, Numerical Analysis (math.NA), neural operator, 01 natural sciences, Algorithms for approximation of functions, AI4science, 0103 physical sciences, FOS: Mathematics, Mathematics - Numerical Analysis, Numerical solution of discretized equations for initial value and initial-boundary value problems involving PDEs, 0101 mathematics, Artificial neural networks and deep learning

Popis souboru: application/xml

Přístupová URL adresa: http://arxiv.org/abs/2206.12698
https://zbmath.org/7883828
https://doi.org/10.1137/23m1556320