Author

Peng-Xiang Du

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#machine learning Preprint Mar 2026

Bridging Theory and Data: Correcting Nuclear Mass Models with Interpretable Machine Learning

This study introduces the Kolmogorov-Arnold Network (KAN) into the refinement of nuclear mass models, proposing an efficient and interpretable solution that provides a novel approach to small-sample, high-complexity scientific problems.

Yan-Hua Lu, Tian-Shuai Shang, Peng-Xiang Du et al. · 0 citations