Understanding charge radii with machine learning: Discovering physics expressions

We introduce a robust, interpretable machine learning (ML) framework that combines numerical regression for high-accuracy predictions with symbolic regression to uncover the underlying physics. This hybrid approach effciently derives analytical expressions by leveraging the smoothed predictions of o...

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Autori principali:	B. Maheshwari, P. Van Isacker
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Elsevier 2026-01-01
Serie:	Physics Letters B
Soggetti:	Charge radii Machine learning Light gradient boosting machine Gaussian process regression Symbolic regression
Accesso online:	http://www.sciencedirect.com/science/article/pii/S0370269325008597
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