4 papers
Learning Informed Prior Distributions with Normalizing Flows for Bayesian Analysis
Hendrik Roch, Chun Shen
We investigate the use of normalizing flow (NF) models as flexible priors in Bayesian inference via Markov Chain Monte Carlo (MCMC) sampling for iterative Bayesian calibration. Tra…
Bayesian Model Selection and Uncertainty Propagation for Beam Energy Scan Heavy-Ion Collisions
Syed Afrid Jahan, Hendrik Roch, Chun Shen
We apply the Bayesian model selection method (based on the Bayes factor) to optimize -dependence in the phenomenological parameters of the (3+1)-dimensional h…
A Gaussian Process Generative Model for QCD Equation of State
Jiaxuan Gong, Hendrik Roch, Chun Shen
We develop a generative model for the nuclear matter equation of state at zero net baryon density using the Gaussian Process Regression method. We impose first-principles theoretic…
On model emulation and closure tests for 3+1D relativistic heavy-ion collisions
Hendrik Roch, Syed Afrid Jahan, Chun Shen
In nuclear and particle physics, reconciling sophisticated simulations with experimental data is vital for understanding complex systems like the Quark Gluon Plasma (QGP) generated…