De Rham compatible deep neural network FEM
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Publication:6057971
DOI10.1016/j.neunet.2023.06.008arXiv2201.05395OpenAlexW4380078591MaRDI QIDQ6057971
Marcello Longo, Nico Disch, Christoph Schwab, J. Zech, Joost A. A. Opschoor
Publication date: 26 October 2023
Published in: Neural Networks (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2201.05395
Artificial neural networks and deep learning (68T07) Finite element, Galerkin and related methods applied to problems in optics and electromagnetic theory (78M10) Finite element, Rayleigh-Ritz and Galerkin methods for initial value and initial-boundary value problems involving PDEs (65M60) de Rham theory in global analysis (58A12)
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