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Improved surrogates in inertial confinement fusion with manifold and cycle consistencies
Neural networks have become the method of choice in surrogate modeling because of their ability to characterize arbitrary, high-dimensional functions in a data-driven fashion. This paper advocates for the training of surrogates that are 1) consistent with the physical manifold, resulting in physical...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
National Academy of Sciences
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7211929/ https://www.ncbi.nlm.nih.gov/pubmed/32312816 http://dx.doi.org/10.1073/pnas.1916634117 |