2 papers
nucl-th2025
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-th2025
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…