9 citations · 11 across the 7 of their papers we have counts for
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nucl-th2026
Combined Garvey Kelson Relations for Mass Determinations and Machine Learning
I. Bentley, A. Fiorito, M. Gebran +2
Simple Garvey Kelson mass relations applied in two regions are often used as an evaluation metric for machine learning based mass models. These relations have also been used in the…
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…
nucl-th2024★ 9 cited
High Precision Binding Energies from Physics Informed Machine Learning
Ian Bentley, James Tedder, Marwan Gebran +1
Twelve physics-informed machine learning models have been trained to model binding energy residuals. Our approach begins with determining the difference between measured experiment…