237 citations · 2.3k across the 83 of their papers we have counts for
5 papers · 1 filter
Implicit Quantile Neural Networks for Jet Simulation and Correction
Braden Kronheim, Michelle P. Kuchera, Harrison B. Prosper +1
Reliable modeling of conditional densities is important for quantitative scientific fields such as particle physics. In domains outside physics, implicit quantile neural networks (…
Response of a CMS HGCAL silicon-pad electromagnetic calorimeter prototype to 20-300 GeV positrons
B. Acar, G. Adamov, C. Adloff +385
The Compact Muon Solenoid Collaboration is designing a new high-granularity endcap calorimeter, HGCAL, to be installed later this decade. As part of this development work, a protot…
Publishing statistical models: Getting the most out of particle physics experiments
Kyle Cranmer, Sabine Kraml, Harrison B. Prosper +30
The statistical models used to derive the results of experimental analyses are of incredible scientific value and are essential information for analysis preservation and reuse. In…
Recent advances in ADL, CutLang and adl2tnm
Harrison B. Prosper, Sezen Sekmen, Gokhan Unel +1
This paper presents an overview and features of an Analysis Description Language (ADL) designed for HEP data analysis. ADL is a domain specific, declarative language that describes…
Learning from the Pandemic: the Future of Meetings in HEP and Beyond
Mark S. Neubauer, Todd Adams, Jennifer Adelman-McCarthy +36
The COVID-19 pandemic has by-and-large prevented in-person meetings since March 2020. While the increasing deployment of effective vaccines around the world is a very positive deve…