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December 6, 2024 Valentin Munteanu, Vladimir Starostin, Alexander Gerlach, Dmitry Lapkin, Alexander Hinderhofer, Frank Schreiber

Human-guided Neural Networks for Synchrotron Experiments

Synchrotron sources produce intense X-rays that are indispensable for many fields of modern science. The essential information, which is often buried in an ocean of experimental data, can be extracted using machine learning. But such models still lack important insights about the structure of the systems being studied. By allowing experimentalists to provide such insights to adaptive neural networks, we were able to instantly obtain more accurate results.
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