8 citations · 10 across the 4 of their papers we have counts for
4 papers
Learning Broken Symmetries with Approximate Invariance
Seth Nabat, Aishik Ghosh, Edmund Witkowski +2
Recognizing symmetries in data allows for significant boosts in neural network training, which is especially important where training data are limited. In many cases, however, the…
Learning Broken Symmetries with Resimulation and Encouraged Invariance
Edmund Witkowski, Daniel Whiteson
Recognizing symmetries in data allows for significant boosts in neural network training. In many cases, however, the underlying symmetry is present only in an idealized dataset, an…
Learning to Isolate Muons in Data
Edmund Witkowski, Benjamin Nachman, Daniel Whiteson
We use unlabeled collision data and weakly-supervised learning to train models which can distinguish prompt muons from non-prompt muons using patterns of low-level particle activit…
Learning to Isolate Muons
Julian Collado, Kevin Bauer, Edmund Witkowski +3
Distinguishing between prompt muons produced in heavy boson decay and muons produced in association with heavy-flavor jet production is an important task in analysis of collider ph…