3 papers
cs.LG2025
Towards Foundation Models for Experimental Readout Systems Combining Discrete and Continuous Data
James Giroux, Cristiano Fanelli
We present a (proto) Foundation Model for Nuclear Physics, capable of operating on low-level detector inputs from Imaging Cherenkov Detectors at the future Electron Ion Collider. B…
physics.ins-det2025
Generative Models for Fast Simulation of Cherenkov Detectors at the Electron-Ion Collider
James Giroux, Michael Martinez, Cristiano Fanelli
The integration of Deep Learning (DL) into experimental nuclear and particle physics has driven significant progress in simulation and reconstruction workflows. However, traditiona…
cs.LG2024
Uncertainty Quantification with Bayesian Higher Order ReLU KANs
James Giroux, Cristiano Fanelli
We introduce the first method of uncertainty quantification in the domain of Kolmogorov-Arnold Networks, specifically focusing on (Higher Order) ReLUKANs to enhance computational e…