44 citations · 65 across the 21 of their papers we have counts for
4 papers · 1 filter
Look everywhere effects in anomaly detection
Marie Hein, Benjamin Nachman, David Shih
Machine learning-based anomaly detection methods are able to search high-dimensional spaces for hints of new physics with much less theory bias than traditional searches. However,…
Fair Universe Higgs Uncertainty Challenge
Ragansu Chakkappai, Wahid Bhimji, Paolo Calafiura +16
This competition in high-energy physics (HEP) and machine learning was the first to strongly emphasise uncertainties in cross-section measurement. Partici…
Discriminative versus Generative Approaches to Simulation-based Inference
Benjamin Sluijter, Sascha Diefenbacher, Wahid Bhimji +1
Most of the fundamental, emergent, and phenomenological parameters of particle and nuclear physics are determined through parametric template fits. Simulations are used to populate…
Optimizers for Stabilizing Likelihood-free Inference
G. Bruno De Luca, Benjamin Nachman, Eva Silverstein +1
A growing number of applications in particle physics and beyond use neural networks as unbinned likelihood ratio estimators applied to real or simulated data. Precision requirement…