Information and Statistics for Nuclear Experiment and Theory workshop (ISNET-9)

Session

ISNET: Poster Session

25 May 2023, 16:45

Washington University in St. Louis

Description

Andrew Gordeev: Bayesian parameter estimation of QGP viscosities in partial chemical equilibrium
Denielle Ricciardi: Accounting for material and experimental variability using a random effects bayesian inferential framework
Hannah Göttling: Gaussian processes for the nuclear equation of state
Mookyong Son: Variational Bayes Computer Models
Yehu Chen: Active learning for marginal effect estimation with Gaussian Process preference learning

49. Accounting for Material and Experimental Variability Using a Random Effects Bayesian Inferential Framework

Denielle Ricciardi

48. Bayesian parameter estimation of QGP viscosities in partial chemical equilibrium

Andrew Gordeev

50. Gaussian processes for the nuclear equation of state

Hannah Göttling

51. Nuclear Binding energy prediction using Deep Learning on AME2020 dataset

Ramesh Bhandari

52. Variational Bayes Computer Models

Mookyong Son