GraphNeT: Graph neural networks for neutrino telescope event reconstruction-Reference-Cited by-同舟云学术

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GraphNeT: Graph neural networks for neutrino telescope event reconstruction

Published:2023-05-12 Issue:85 Volume:8 Page:4971
ISSN:2475-9066
Container-title:Journal of Open Source Software
language:
Short-container-title:JOSS

Author:

Søgaard Andreas^ORCID,Ørsøe Rasmus F.^ORCID,Holm Morten^ORCID,Bozianu Leon^ORCID,Rosted Aske^ORCID,Petersen Troels C.^ORCID,Iversen Kaare Endrup^ORCID,Hermansen Andreas^ORCID,Guggenmos Tim,Andresen Peter^ORCID,Minh Martin Ha^ORCID,Neste Ludwig^ORCID,Holmes Moust^ORCID,Pontén Axel^ORCID,DeHolton Kayla Leonard^ORCID,Eller Philipp^ORCID

Publisher

The Open Journal

Subject

General Earth and Planetary Sciences,General Environmental Science

Link

https://joss.theoj.org/papers/10.21105/joss.04971.pdf

Reference28 articles.

1. GraphNeT;Søgaard,2023

2. PyTorch: An imperative style, high-performance deep learning library;Paszke;Advances in neural information processing systems 32,2019

3. Fast Graph Representation Learning with PyTorch Geometric;Fey,2019

4. PyTorch Lightning;Falcon,2019

5. Experiment tracking with weights and biases;Biewald,2020

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. New limits on neutrino decay from high-energy astrophysical neutrinos;Physical Review D;2024-08-02

2. IceCube – Neutrinos in Deep Ice;The European Physical Journal C;2024-06-25

3. Refine neutrino events reconstruction with BEiT-3;Journal of Instrumentation;2024-06-01

4. Event Reconstruction for Neutrino Telescopes;Machine Learning for Astrophysics;2023

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