21 citations · 21 across the 2 of their papers we have counts for
2 papers
nucl-th2025
Machine Learning for Correlations of Electromagnetic Properties in Ab Initio Calculations
Marco Knöll, Marc L. Agel, Tobias Wolfgruber +2
In ab initio nuclear structure theory, accurately predicting electromagnetic observables, such as moments and transition rates, is essential for a comprehensive understanding of nu…
nucl-th2022★ 21 cited
Machine Learning for the Prediction of Converged Energies from Ab Initio Nuclear Structure Calculations
Marco Knöll, Tobias Wolfgruber, Marc L. Agel +2
The prediction of nuclear observables beyond the finite model spaces that are accessible through modern ab initio methods, such as the no-core shell model, pose a challenging task…