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Generalized neural closure models with interpretability
Improving the predictive capability and computational cost of dynamical models is often at the heart of augmenting computational physics with machine learning (ML). However, most learning results are limited in interpretability and generalization over different computational grid resolutions, initia...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group UK
2023
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10313723/ https://www.ncbi.nlm.nih.gov/pubmed/37391424 http://dx.doi.org/10.1038/s41598-023-35319-w |