2 papers
cs.LG2025
Neural Architecture Codesign for Fast Physics Applications
Jason Weitz, Dmitri Demler, Luke McDermott +2
We develop a pipeline to streamline neural architecture codesign for physics applications to reduce the need for ML expertise when designing models for novel tasks. Our method empl…
physics.ins-det2025
Track reconstruction as a service for collider physics
Haoran Zhao, Yuan-Tang Chou, Yao Yao +11
Optimizing charged-particle track reconstruction algorithms is crucial for efficient event reconstruction in Large Hadron Collider (LHC) experiments due to their significant comput…