83 citations · 85 across the 13 of their papers we have counts for
4 papers · 1 filter
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…
Distributed statistical inference with pyhf enabled through funcX
Matthew Feickert, Lukas Heinrich, Giordon Stark +1
In High Energy Physics facilities that provide High Performance Computing environments provide an opportunity to efficiently perform the statistical inference required for analysis…
Software Training in HEP
Sudhir Malik, Samuel Meehan, Kilian Lieret +44
Long term sustainability of the high energy physics (HEP) research software ecosystem is essential for the field. With upgrades and new facilities coming online throughout the 2020…
A Living Review of Machine Learning for Particle Physics
Matthew Feickert, Benjamin Nachman
Modern machine learning techniques, including deep learning, are rapidly being applied, adapted, and developed for high energy physics. Given the fast pace of this research, we hav…