Jonathan Renusch

Fast and Precise Learned Charged-Particle Trajectory Regression at the Large Hadron Collider

We propose a training recipe that treats charged-particle trajectory parameter regression on high-energy physics detector data as a sequence-modeling task. Kalman filters and linearized least-squares fits have been the classical standard approach for this task: they are optimal estimators for sparsely sampled linear-Ga...