297 citations · 880 across the 30 of their papers we have counts for
3 papers · 1 filter
Uncertainty Aware Learning for High Energy Physics
Aishik Ghosh, Benjamin Nachman, Daniel Whiteson
Machine learning techniques are becoming an integral component of data analysis in High Energy Physics (HEP). These tools provide a significant improvement in sensitivity over trad…
E Pluribus Unum Ex Machina: Learning from Many Collider Events at Once
Benjamin Nachman, Jesse Thaler
There have been a number of recent proposals to enhance the performance of machine learning strategies for collider physics by combining many distinct events into a single ensemble…
Parametrizing the Detector Response with Neural Networks
Sanha Cheong, Aviv Cukierman, Benjamin Nachman +2
In high energy physics, characterizing the response of a detector to radiation is one of the most important and basic experimental tasks. In many cases, this task is accomplished b…