33 citations · 44 across the 4 of their papers we have counts for
4 papers
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…
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…
The BlackGEM telescope array I: Overview
Paul J. Groot, S. Bloemen, P. Vreeswijk +75
The main science aim of the BlackGEM array is to detect optical counterparts to gravitational wave mergers. Additionally, the array will perform a set of synoptic surveys to detect…
FINKER: Frequency Identification through Nonparametric KErnel Regression in astronomical time series
F. Stoppa, C. Johnston, E. Cator +2
Optimal frequency identification in astronomical datasets is crucial for variable star studies, exoplanet detection, and asteroseismology. Traditional period-finding methods often…