TrackML: A High Energy Physics Particle Tracking Challenge-Reference-Cited by-同舟云学术

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TrackML: A High Energy Physics Particle Tracking Challenge

Published:2018-10 Issue: Volume: Page:
ISSN:
Container-title:2018 IEEE 14th International Conference on e-Science (e-Science)
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Author:

Calafiura Polo,Farrell Steven,Gray Heather,Vlimant Jean-Roch,Innocente Vincenzo,Salzburger Andreas,Amrouche Sabrina,Golling Tobias,Kiehn Moritz,Estrade Victor,Germaint Cecile,Guyon Isabelle,Moyse Ed,Rousseau David,Yilmaz Yetkin,Gligorov Vladimir Vava,Hushchyn Mikhail,Ustyuzhanin Andrey

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8588285/8588619/08588707.pdf?arnumber=8588707

Cited by 5 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. The study of intelligent algorithm in particle identification of heavy-ion collisions at low and intermediate energies;Nuclear Science and Techniques;2024-02

2. The Generic Collective Intelligence Framework: A Qualitative View;SSRN Electronic Journal;2023

3. Combustion machine learning: Principles, progress and prospects;Progress in Energy and Combustion Science;2022-07

4. Applications and Techniques for Fast Machine Learning in Science;Frontiers in Big Data;2022-04-12

5. Charged particle tracking with quantum annealing optimization;Quantum Machine Intelligence;2021-11-02

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