99 citations · 191 across the 16 of their papers we have counts for
16 papers
CaloTrilogy: Toward a Breakthrough in One-Step, End-to-End, Physics-Guided Shower Generation for Modern Calorimeters
Cheng Jiang, Sitian Qian, Kevin Pedro +3
High-precision calorimeter simulation at current and future colliders imposes rapidly growing computational demands, motivating the development of machine-learning surrogates for t…
Model-Agnostic Signal Discovery with Machine Learning: Bridging the Gap Between Theory and Practice
Oz Amram, Marco Letizia, Mikael Kuusela
Searches for new phenomena in complex scientific data are predominantly model-dependent, optimized for specific hypotheses, and therefore limited in their coverage of the space of…
Neural Scaling Laws for Jet Generation
Oz Amram, Darius A. Faroughy, Tjarko Gerdes +5
Recently observed empirical scaling laws describe the performance of foundation-type models as three independent key quantities -- dataset size, compute, and model parameters -- ar…
Building an AI-native Research Ecosystem for Experimental Particle Physics: A Community Vision
Thea Klaeboe Aarrestad, Alaa Abdelhamid, Haider Abidi +457
Experimental particle physics seeks to understand the universe by probing its fundamental particles and forces and exploring how they govern the large-scale processes that shape co…
Data-Driven High-Dimensional Statistical Inference with Generative Models
Oz Amram, Manuel Szewc
Crucial to many measurements at the LHC is the use of correlated multi-dimensional information to distinguish rare processes from large backgrounds, which is complicated by the poo…
United States Muon Collider Community White Paper for the European Strategy for Particle Physics Update
A. Abdelhamid, D. Acosta, P. Affleck +301
This document is being submitted to the 2024-2026 European Strategy for Particle Physics Update (ESPPU) process on behalf of the US Muon Collider community, with its preparation co…