uncertainty quantification
· 15 papers, 7 presentations · all tags
Papers filter the publication list
- ENDF/B-VIII.1: updated nuclear reaction data library for science and applications
- Reducing parametric uncertainties through information geometry methods
- An optical-lensing inspired data thinning method for nuclear cross section data
- Constraining nuclear mass models using r-process observables with multi-objective optimization
- Emulation of the final r-process abundance pattern with a neural network
- Investigating the effects of precise mass measurements of Ru and Pd isotopes on machine learning mass modeling
- Nuclear uncertainties associated with the ejecta of a black-hole accretion disk
- Uncertainty quantification of mass models using Ensemble Bayesian Model Averaging
- Bayesian averaging for ground state masses of atomic nuclei in a Machine Learning approach
- Uncertainties in kilonova modeling
- Nuclear data activities for medium mass and heavy nuclei at Los Alamos
- Measuring the $\beta$-decay properties of neutron-rich exotic Pm, Sm, Eu, and Gd isotopes to constrain the nucleosynthesis yields in the rare-earth region
- Nuclear masses learned from a probabilistic neural network
- Propagation of statistical uncertainties of Skyrme mass models to simulations of $r$-process nucleosynthesis
- Variances in $r$-process predictions from uncertain nuclear rates
Presentations filter the presentation list
- Nuclear uncertainties associated with the ejecta of a black-hole accretion disk
- Machine learning and uncertainty quantification for ground state masses
- Covariances for the LANL $^{239}$Pu cross section evaluation
- Nuclear data activities for medium mass and heavy nuclei at Los Alamos
- Machine Learning and Artificial Intelligence for computational nuclear data
- Novel Bayesian inference techniques and their implementation at LANL
- Error bars on $r$-process abundances from uncertain nuclear masses