8 citations · 8 across the 5 of their papers we have counts for
5 papers
Machine Learning Enhanced Detection of Higgs Chain Decays in Vector Boson Fusion
Shreecheta Chowdhury, Amit Chakraborty, Stefano Moretti
Over the years, Vector Boson Fusion (VBF) has established itself as one of the most robust production channels for studying the Higgs boson, while also serving as a promising pathw…
Interference Effects in Resonant Standard Model di-Higgs Production and Decay into Final States: the Role of Machine Learning Analysis
A. Hammad, S. Moretti, A. P. Przybyl +1
The final state with four -quarks has generally the largest event rate in Standard Model (SM)-like Higgs () pair production, but also the largest backgrounds. We stu…
Explaining Data Anomalies over the NMSSM Parameter Space with Deep Learning Techniques
A. Hammad, Raymundo Ramos, Amit Chakraborty +2
Motivated by recent results from particle physics analyses, we investigate the Next-to-Minimal Supersymmetric Standard Model (NMSSM) as a framework capable of accommodating a range…
Multi-scale cross-attention transformer encoder for event classification
A. Hammad, S. Moretti, M. Nojiri
We deploy an advanced Machine Learning (ML) environment, leveraging a multi-scale cross-attention encoder for event classification, towards the identification of the $gg\to H\to hh…
Search for Mono-Higgs Signals in Final States Using Deep Neural Networks
A. Hammad, S. Khalil, S. Moretti
We study mono-Higgs signatures emerging in an illustrative new physics scenario involving Standard Model Higgs boson decays to bottom quark pairs using Hybrid Deep Neural Networks.…