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An adaptive approach to machine learning for compact particle accelerators
Machine learning (ML) tools are able to learn relationships between the inputs and outputs of large complex systems directly from data. However, for time-varying systems, the predictive capabilities of ML tools degrade if the systems are no longer accurately represented by the data with which the ML...
Autores principales: | Scheinker, Alexander, Cropp, Frederick, Paiagua, Sergio, Filippetto, Daniele |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8478924/ https://www.ncbi.nlm.nih.gov/pubmed/34584162 http://dx.doi.org/10.1038/s41598-021-98785-0 |
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