52 citations · 165 across the 14 of their papers we have counts for
3 papers · 1 filter
Locality-Sensitive Hashing-Based Efficient Point Transformer for Charged Particle Reconstruction
Shitij Govil, Jack P. Rodgers, Yuan-Tang Chou +9
Charged particle track reconstruction is a foundational task in collider experiments and the main computational bottleneck in particle reconstruction. Graph neural networks (GNNs)…
Graph Neural Networks in Particle Physics: Implementations, Innovations, and Challenges
Savannah Thais, Paolo Calafiura, Grigorios Chachamis +7
Many physical systems can be best understood as sets of discrete data with associated relationships. Where previously these sets of data have been formulated as series or image dat…
Charged particle tracking via edge-classifying interaction networks
Gage DeZoort, Savannah Thais, Javier Duarte +5
Recent work has demonstrated that geometric deep learning methods such as graph neural networks (GNNs) are well suited to address a variety of reconstruction problems in high energ…