Circella M, Eberl T (2022)
Publication Language: English
Publication Type: Journal article, Original article
Subtype: other
Publication year: 2022
Book Volume: 53
Pages Range: 26-29-29
Journal Issue: 2
DOI: 10.1051/epn/2022206
Deep in the water of the Mediterranean Sea, the KM3NeT detectors aim at the exploration of the cosmos through the detection of neutrinos and to determine the neutrino mass ordering. Machine learning techniques are widely used to push the performance of the detectors to the limit.
APA:
Circella, M., & Eberl, T. (2022). Machine learning techniques deep underwater in km3net. Europhysics News, 53(2), 26-29-29. https://doi.org/10.1051/epn/2022206
MLA:
Circella, Marco, and Thomas Eberl. "Machine learning techniques deep underwater in km3net." Europhysics News 53.2 (2022): 26-29-29.
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