2 papers
hep-ex2026
How to scale your HEP ML models: A recipe for robust architecture comparisons at scale
Matthias Vigl, Nikita Pond, Jackson Barr +5
Much of the recent progress in machine learning domains such as language models has come from scaling laws that predict performance as a function of training effort. In high-energy…
hep-ex2021
Software Training in HEP
Sudhir Malik, Samuel Meehan, Kilian Lieret +44
Long term sustainability of the high energy physics (HEP) research software ecosystem is essential for the field. With upgrades and new facilities coming online throughout the 2020…