An adaptive approach to machine learning for compact particle accelerators

Abstract 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 whi...

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Bibliographic Details
Main Authors: Alexander Scheinker, Frederick Cropp, Sergio Paiagua, Daniele Filippetto
Format: Article
Language:English
Published: Nature Publishing Group 2021-09-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-98785-0