2 citations · 2 across the 2 of their papers we have counts for
2 papers
physics.ins-det2026
Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP)
Julia Gonski, Jennifer Ott, Jenni Ott +129
The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environmen…
cs.LG2024★ 2 cited
Investigating Resource-efficient Neutron/Gamma Classification ML Models Targeting eFPGAs
Jyothisraj Johnson, Billy Boxer, Tarun Prakash +3
There has been considerable interest and resulting progress in implementing machine learning (ML) models in hardware over the last several years from the particle and nuclear physi…