2 citations · 2 across the 8 of their papers we have counts for
4 papers · 1 filter
Searching for BSM Experimental Signatures with Large Lagrangian Models
Ibrahim Elsharkawy, Victoria Knapp-Perez, Wahid Bhimji +1
The search for physics Beyond the Standard Model (BSM) is generally limited not by the supply of theory descriptions but by the lack of discriminating experimental observations. A…
Pre-Training for Simulation-Based Science: A Study on Jet Foundation Model Training Objectives
Ibrahim Elsharkawy, Joschka Birk, Vinicius Mikuni +3
Foundation models (FMs) trained on large datasets and fine-tuned on downstream tasks have emerged as a powerful paradigm in AI for science. Industrial FMs are typically trained usi…
Generative models on phase space
Zachary Bogorad, Ibrahim Elsharkawy, Yonatan Kahn +2
Deep generative models such as diffusion and flow matching are powerful machine learning tools capable of learning and sampling from high-dimensional distributions. They are partic…
FAIR Universe HiggsML Uncertainty Dataset and Competition
Lisa Benato, Wahid Bhimji, Paolo Calafiura +26
The FAIR Universe HiggsML Uncertainty Challenge focused on measuring the physical properties of elementary particles with imperfect simulators. Participants were required to comput…