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Scaling laws for neural networks applied to particle physics amplitude surrogates

By PulseAugur Editorial · [1 sources] ·

Researchers have investigated scaling laws for neural networks specifically applied to amplitude surrogates in particle physics. Their findings indicate a connection between scaling coefficients and the number of external particles in a given process. The study demonstrates that these scaling laws are a valuable method for achieving precise targets in this domain. AI

RANK_REASON This is a research paper published on arXiv detailing scientific findings. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Scaling laws for neural networks applied to particle physics amplitude surrogates

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This is a research paper published on arXiv detailing scientific findings. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Henning Bahl, Victor Bres\'o-Pla, Anja Butter, Joaqu\'in Iturriza Ramirez ·

    Scaling laws for amplitude surrogates

    arXiv:2601.13308v2 Announce Type: replace-cross Abstract: Scaling laws describing the dependence of neural network performance on the amount of training data, the spent compute, and the network size have emerged across a huge variety of machine learning task and datasets. In this…

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