3 papers
astro-ph.SR2025
TheUse of Conditional Variational Autoencoders in Generating Stellar Spectra
Marwan Gebran, Ian Bentley
We present a conditional variational autoencoder (CVAE) that generates stellar spectra covering 4000 $T_{\mathrm{eff}$ 11,000 K, dex, $-1.5 \le…
astro-ph.SR2024
Deep Learning application for stellar parameters determination: III- Denoising Procedure
Marwan Gebran, Ian Bentley, Rose Brienza +1
In this third paper in a series, we investigate the need of spectra denoising for the derivation of stellar parameters. We have used two distinct datasets for this work. The first…
nucl-th2024
High Precision Binding Energies from Physics Informed Machine Learning
Ian Bentley, James Tedder, Marwan Gebran +1
Twelve physics-informed machine learning models have been trained to model binding energy residuals. Our approach begins with determining the difference between measured experiment…