A graph convolutional autoencoder approach to model order reduction for parametrized PDEs
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Publication:6126547
DOI10.1016/j.jcp.2024.112762arXiv2305.08573OpenAlexW4390843165MaRDI QIDQ6126547
Jan S. Hesthaven, Beatriz Moya, Federico Pichi
Publication date: 9 April 2024
Published in: Journal of Computational Physics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2305.08573
parametric PDEsgeometrical parametersgraph neural networksconvolutional autoencodernonlinear reduced order modeling
Artificial intelligence (68Txx) Numerical methods for partial differential equations, initial value and time-dependent initial-boundary value problems (65Mxx) Numerical methods for partial differential equations, boundary value problems (65Nxx)
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