Modeling turbulent and self-gravitating fluids with Fourier neural operators
Neural Operators (NOs) are a leading method for surrogate modeling of partial differential equations. Unlike traditional neural networks, which approximate individual functions, NOs learn the mappings between function spaces. While NOs have been predominantly tested on simplified 1D and 2D problems,...
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| Autori principali: | , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
AIP Publishing LLC
2025-06-01
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| Serie: | APL Machine Learning |
| Accesso online: | http://dx.doi.org/10.1063/5.0263607 |
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