833 citations · 958 across the 5 of their papers we have counts for
Showing 2020Show all
2 papers · 1 filter
nucl-th2020★ 13 cited
Optimization and Supervised Machine Learning Methods for Fitting Numerical Physics Models without Derivatives
Raghu Bollapragada, Matt Menickelly, Witold Nazarewicz +3
We address the calibration of a computationally expensive nuclear physics model for which derivative information with respect to the fit parameters is not readily available. Of par…
nucl-th2020★ 10 cited
Calibration of Energy Density Functionals with Deformed Nuclei
N. Schunck, J. O'Neal, M. Grosskopf +2
Nuclear density functional theory is the prevalent theoretical framework for accurately describing nuclear properties at the scale of the entire chart of nuclides. Given an energy…