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20242026
most citedHigh Precision Binding Energies from Physics Informed Machine Learning

9 citations · 11 across the 7 of their papers we have counts for

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astro-ph.SR2025

TheUse of Conditional Variational Autoencoders in Generating Stellar Spectra

Marwan Gebran, Ian Bentley

We present a conditional variational autoencoder (CVAE) that generates stellar spectra covering 4000 $T_{\mathrm{eff}$ 11,000 K, dex, $-1.5 \le…

nucl-th2025★ 2 cited

Further exploration of binding energy residuals using machine learning and the development of a composite ensemble model

I. Bentley, J. Tedder, M. Gebran +1

This paper describes the development of the Four Model Tree Ensemble (FMTE). The FMTE is a composite of machine learning models trained on experimental binding energies from the At…