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Machine learning enabling high-throughput and remote operations at large-scale user facilities
Imaging, scattering, and spectroscopy are fundamental in understanding and discovering new functional materials. Contemporary innovations in automation and experimental techniques have led to these measurements being performed much faster and with higher resolution, thus producing vast amounts of data for analysis. These innovations are particularly pronounced at user facilities and synchrotron light sources. Machine learning (ML) methods are regularly developed to process and interpret largedoi:10.48550/arxiv.2201.03550 fatcat:ydmyepic5feffdrxnqc5pmi2di