19 citations · 19 across the 4 of their papers we have counts for
4 papers
Restricted Boltzmann Machines Propagators for Auxiliary Field Diffusion Monte Carlo
Jordan M. R. Fox, Alessandro Lovato, Alessandro Roggero +1
The auxiliary field diffusion Monte Carlo method uses imaginary-time projection techniques to accurately solve the ground-state wave function of atomic nuclei and infinite nuclear…
Illuminating Systematic Trends in Nuclear Data with Generative Machine Learning Models
Jordan M. R. Fox, Kyle A. Wendt
We introduce a novel method for studying systematic trends in nuclear reaction data using generative adversarial networks. Libraries of nuclear cross section evaluations exhibit in…
Uncertainty quantification of transition operators in the empirical shell model
Jordan M. R. Fox, Calvin W. Johnson, Rodrigo Navarro Perez
While empirical shell model calculations have successfully described low-lying nuclear data for decades, only recently has significant effort been made to quantify the uncertainty…
Uncertainty quantification of an empirical shell-model interaction using principal component analysis
Jordan M. R. Fox, Calvin W. Johnson, Rodrigo Navarro Perez
Recent investigations have emphasized the importance of uncertainty quantification (UQ) to describe errors in nuclear theory. We carry out UQ for configuration-interaction shell mo…