Perspectives for machine learning applied to data-rich experiments on complex 
materials

Freysoldt, Christoph; Katnagallu, Shyam; Neugebauer, Jörg; Mishra, Arpit; Ashton, Michael W.

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Perspectives for machine learning applied to data-rich experiments on complex materials

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Freysoldt, Christoph
Defect Chemistry and Spectroscopy, Computational Materials Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Katnagallu, Shyam
Defect Chemistry and Spectroscopy, Computational Materials Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Neugebauer, Jörg
Computational Materials Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Mishra, Arpit
Defect Chemistry and Spectroscopy, Computational Materials Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Ashton, Michael W.
Defect Chemistry and Spectroscopy, Computational Materials Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Freysoldt, C., Katnagallu, S., Neugebauer, J., Mishra, A., & Ashton, M. W. (2024). Perspectives for machine learning applied to data-rich experiments on complex materials. Talk presented at Workshop on local probes of chemical bonding and atom probe tomography at RWTH Aachen. Aachen, Germany. 2024-06-12 - 2024-06-14.

Cite as: https://hdl.handle.net/21.11116/0000-000F-A993-C

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