77 citations · 86 across the 7 of their papers we have counts for
3 papers · 1 filter
Direct Vertex Reconstruction of Baryons from Hits in CLAS12 using Graph Neural Networks
Keegan Menkce, Matthew McEneaney, Anselm Vossen
Machine learning techniques, including Graph Neural Networks (GNNs), have been used extensively for data analysis in high energy and nuclear physics. Here we report on the use of a…
Improving Signal Extraction with Domain Adaptation via Normalizing Flows
Rowan Kelleher, Matthew McEneaney, Anselm Vossen
The present study presents a novel application for normalizing flows for domain adaptation. The study investigates the ability of flow based neural networks to improve signal extra…
Domain-Adversarial Graph Neural Networks for Hyperon Identification with CLAS12
Matthew McEneaney, Anselm Vossen
Machine learning methods and in particular Graph Neural Networks (GNNs) have revolutionized many tasks within the high energy physics community. We report on the novel use of GNNs…