3 citations · 6 across the 7 of their papers we have counts for
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Machine Learning-Informed 3+1 Sterile Neutrino Global Fits using Posterior Density Estimation of Electron Disappearance Data
Joshua Villarreal, Julia Woodward, John Hardin +1
Global analyses of particle physics data are integral for validating and scrutinizing published results of experiments. Global fits of anomalous oscillation data which search for o…
A Frequentist Simulation-Based Inference Treatment of Sterile Neutrino Global Fits
Joshua Villarreal, Julia Woodward, John Hardin +1
A critical challenge in particle physics is combining results from diverse experimental setups that measure the same physical quantity to enhance precision and statistical power, a…
Feldman-Cousins' ML Cousin: Sterile Neutrino Global Fits using Simulation-Based Inference
Joshua Villarreal, John M. Hardin, Janet M. Conrad
For many small-signal particle physics analyses, Wilks' theorem, a simplifying assumption that presumes log-likelihood asymptotic normality, does not hold. The most common alternat…