arXiv Machine Learning June 30, 2026 By M. Rejmund (GANIL, CEA/DRF - CNRS/IN2P3, Bd Henri Becquerel, BP 55027, F-14076, Caen Cedex 5, France), A. Lemasson (GANIL, CEA/DRF - CNRS/IN2P3, Bd Henri Becquerel, BP 55027, F-14076, Caen Cedex 5, France)

Self-Supervised Calibration of Scientific Instruments Using Physical Consistency Constraints

Read the original on arXiv Machine Learning →

arXiv:2606. 29466v1 Announce Type: new Abstract: Calibration remains one of the principal obstacles to the deployment of machine learning in scientific instrumentation because it typically relies on expert intervention, dedicated procedures, and manually labelled data.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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