par Abbasi, Rasha;Schlüter, Felix 
;Toscano, Simona ; [et al.]
Référence (26 July 2023 through 3 August 2023: Nagoya), 38th International Cosmic Ray Conference, ICRC 2023, Pos proceedings of science (444), 1609
Publication Publié, 2024-02-01
;Toscano, Simona ; [et al.]Référence (26 July 2023 through 3 August 2023: Nagoya), 38th International Cosmic Ray Conference, ICRC 2023, Pos proceedings of science (444), 1609
Publication Publié, 2024-02-01
Publication dans des actes
| Résumé : | 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. |
