Public Kaggle Competition “IceCube - Neutrinos in Deep ice”
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(Published version)
Date
2024
Authors
Eller, P.
Abbasi, R.
Ackermann, M.
Adams, J.
Agarwalla, S.K.
Aguilar, J.A.
Ahlers, M.
Alameddine, J.M.
Amin, N.M.
Andeen, K.
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Conference paper
Citation
Proceedings of Science, 2024, vol.444, pp.1609-1-1609-11
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International Cosmic Ray Conference (ICRC) (26 Jul 2023 - 3 Aug 2023 : Nagoya, Japan)
Abstract
The reconstruction of neutrino events in the IceCube experiment is crucial for many scientific analyses, including searches for cosmic neutrino sources. The Kaggle competition "IceCube - Neutrinos in Deep ice" was a public machine learning challenge designed to encourage the development of innovative solutions to improve the accuracy and efficiency of neutrino event reconstruction. Participants worked with a dataset of simulated neutrino events and were tasked with creating a suitable model to predict the direction vector of incoming neutrinos. From January to April 2023, hundreds of teams competed for a total of $50k prize money, which was awarded to the best performing few out of the many thousand submissions. In this contribution I will present some insights into the organization of this large outreach project, and summarize some of the main findings, results and takeaways.
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© Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).