7 citations · 10 across the 2 of their papers we have counts for
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astro-ph.SR2025★ 3 cited
Unsupervised learning for variability detection with Gaia DR3 photometry. The main sequence-white dwarf valley
P. Ranaivomanana, C. Johnston, G. Iorio +4
The unprecedented volume and quality of data from space- and ground-based telescopes present an opportunity for machine learning to identify new classes of variable stars and pecul…
astro-ph.SR2024★ 7 cited
Variability in hot sub-luminous stars and binaries: Machine-learning analysis of Gaia DR3 multi-epoch photometry
P. Ranaivomanana, M. Uzundag, C. Johnston +3
Hot sub-luminous stars represent a population of stripped and evolved red giants that is located on the extreme horizontal branch. Since they exhibit a wide range of variability du…