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Cited article:

Application of Machine Learning Methods in Baikal-GVD: Background Noise Rejection and Selection of Neutrino-Induced Events

A. V. Matseiko and I. V. Kharuk
Moscow University Physics Bulletin 78 (S1) S71 (2023)
https://doi.org/10.3103/S0027134923070226

Graph neural network for 3D classification of ambiguities and optical crosstalk in scintillator-based neutrino detectors

Saúl Alonso-Monsalve, Dana Douqa, César Jesús-Valls, et al.
Physical Review D 103 (3) (2021)
https://doi.org/10.1103/PhysRevD.103.032005

The use of Cherenkov light in the detection of high-energy cosmic rays and neutrinos: The Pierre Auger and IceCube Observatories

Lu Lu and Tianlu Yuan
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 970 163678 (2020)
https://doi.org/10.1016/j.nima.2020.163678

Machine learning-based predictions of directionality and charge of cosmic muons—a simulation study using the mICAL detector

D. Samuel, A. Samalan, M. Omana Kuttan and L.P. Murgod
Journal of Instrumentation 14 (11) P11020 (2019)
https://doi.org/10.1088/1748-0221/14/11/P11020