16 citations · 16 across the 4 of their papers we have counts for
4 papers · 1 filter
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…
DLScanner: A parameter space scanner package assisted by deep learning methods
A. Hammad, Raymundo Ramos
In this paper, we introduce a scanner package enhanced by deep learning (DL) techniques. The proposed package addresses two significant challenges associated with previously develo…
LeStrat-Net: Lebesgue style stratification for Monte Carlo simulations powered by machine learning
Kayoung Ban, Myeonghun Park, Raymundo Ramos
We develop a machine learning algorithm to turn around stratification in Monte Carlo sampling. We use a different way to divide the domain space of the integrand, based on the heig…
Exploration of Parameter Spaces Assisted by Machine Learning
A. Hammad, Myeonghun Park, Raymundo Ramos +1
We demonstrate two sampling procedures assisted by machine learning models via regression and classification. The main objective is the use of a neural network to suggest points li…