22 citations · 88 across the 25 of their papers we have counts for
3 papers · 1 filter
Machine Learning-Assisted Unfolding for Neutrino Cross-section Measurements with the OmniFold Technique
Roger G. Huang, Andrew Cudd, Masaki Kawaue +4
The choice of unfolding method for a cross-section measurement is tightly coupled to the model dependence of the efficiency correction and the overall impact of cross-section model…
Parnassus: An Automated Approach to Accurate, Precise, and Fast Detector Simulation and Reconstruction
Etienne Dreyer, Eilam Gross, Dmitrii Kobylianskii +3
Detector simulation and reconstruction are a significant computational bottleneck in particle physics. We develop Particle-flow Neural Assisted Simulations (Parnassus) to address t…
Designing Observables for Measurements with Deep Learning
Owen Long, Benjamin Nachman
Many analyses in particle and nuclear physics use simulations to infer fundamental, effective, or phenomenological parameters of the underlying physics models. When the inference i…