hep-ex · 2026-10-06 · No. 135

High Energy Physics - Experiment, 2026-10-06.

1 new papers in hep-ex. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

1 entries
  1. 01

    How to scale your HEP ML models: A recipe for robust architecture comparisons at scale

    Matthias Vigl, Nikita Pond, Jackson Barr, Alexander Froch, Dan Guest, Nicole Hartman, Michael Kagan, Lukas Heinrich

    hep-ex · cs.LG · hep-ph · physics.data-an

    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 physics (HEP) similar behavior has now been observed. To aid further study, we present a systematic procedure to derive robust scaling laws and compare design choices on the relevant budget axes for HEP tasks. We first validate the full scaling trajectory on toy...

    arxiv.org/abs/2610.06784 · PDF

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