1 citations · 1 across the 4 of their papers we have counts for
4 papers
CoLLM: AI engineering toolbox for end-to-end deep learning in collider analyses
W. Esmail, A. Hammad, M. Nojiri
Recent improvements in large language models have opened new opportunities for accelerating and automating scientific workflows. In parallel, modern collider analyses are becoming…
IAFormer: Interaction-Aware Transformer network for collider data analysis
W. Esmail, A. Hammad, M. Nojiri
In this paper, we introduce \texttt{IAFormer}, a novel Transformer-based architecture that efficiently integrates pairwise particle interactions through a dynamic sparse attention…
Testing CP properties of the Higgs boson coupling to leptons with heterogeneous graphs
W. Esmail, A. Hammad, M. Nojiri +1
We explore the feasibility of measuring the CP properties of the Higgs boson coupling to leptons at the High Luminosity Large Hadron Collider (HL-LHC). Employing detailed Monte…
Sharpening the Signature of the Type-II 2HDM at the LHC through Advanced Machine Learning
W. Esmail, A. Hammad, S. Moretti
The decay signature has been highlighted as possibly being the first testable probe of the Standard Model (SM) Higgs boson discovered in 2012 () interacting with…