FAIR AI models in high energy physics

FAIR AI models in high energy physics

The findable, accessible, interoperable, and reusable (FAIR) data principles provide a framework for examining, evaluating, and improving how data is shared to facilitate scientific discovery. Generalizing these principles to research software and other digital products is an active area of research...

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Bibliographic Details
Main Authors: Javier Duarte, Haoyang Li, Avik Roy, Ruike Zhu, E A Huerta, Daniel Diaz, Philip Harris, Raghav Kansal, Daniel S Katz, Ishaan H Kavoori, Volodymyr V Kindratenko, Farouk Mokhtar, Mark S Neubauer, Sang Eon Park, Melissa Quinnan, Roger Rusack, Zhizhen Zhao
Format: Article
Language:English
Published: IOP Publishing 2023-01-01
Series:Machine Learning: Science and Technology
Subjects:
FAIR
AI
high energy physics
Higgs boson
ML
Online Access:https://doi.org/10.1088/2632-2153/ad12e3

Internet

https://doi.org/10.1088/2632-2153/ad12e3

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