activity
20182023
most citedDirect comparison between Bayesian and frequentist uncertainty quantification for nuclear reactions

84 citations · 156 across the 4 of their papers we have counts for

collaborators

9 papers

nucl-th2020

Statistical aspects of nuclear mass models

Vojtech Kejzlar, Léo Neufcourt, Witold Nazarewicz +1

We study the information content of nuclear masses from the perspective of global models of nuclear binding energies. To this end, we employ a number of statistical methods and dia…

nucl-th2020

Quantified limits of the nuclear landscape

Léo Neufcourt, Yuchen Cao, Samuel A. Giuliani +3

The chart of the nuclides is limited by particle drip lines beyond which nuclear stability to proton or neutron emission is lost. Predicting the range of particle-bound isotopes po…

nucl-th201962 cited

Beyond the proton drip line: Bayesian analysis of proton-emitting nuclei

Léo Neufcourt, Yuchen Cao, Samuel Giuliani +3

The limits of the nuclear landscape are determined by nuclear binding energies. Beyond the proton drip lines, where the separation energy becomes negative, there is not enough bind…

nucl-th201984 cited

Direct comparison between Bayesian and frequentist uncertainty quantification for nuclear reactions

G. B. King, A. E. Lovell, L. Neufcourt +1

Until recently, uncertainty quantification in low energy nuclear theory was typically performed using frequentist approaches. However in the last few years, the field has shifted t…

stat.ME2019

Bayesian averaging of computer models with domain discrepancies: a nuclear physics perspective

Vojtech Kejzlar, Léo Neufcourt, Taps Maiti +1

This article studies Bayesian model averaging (BMA) in the context of competing expensive computer models in a typical nuclear physics setup. While it is well known that BMA accoun…

physics.acc-ph201910 cited

Reconstruction of Storage Ring 's Linear Optics with Bayesian Inference

Yue Hao, Yongjun Li, Michael Balcewicz +2

A novel approach of accurately reconstructing storage ring's linear optics from turn-by-turn (TbT) data containing measurement error is introduced. This approach adopts a Bayesian…