2 papers
astro-ph.GA2026
Feature-driven anomaly flagging in obscured active galactic nucleus light curves with autoencoders
Natale De Bonis, Demetra De Cicco, Stefano Cavuoti +5
Active galactic nuclei (AGN) are among the most complex classes of astrophysical objects, displaying a wide range of variability and observational properties. Identifying unusual A…
astro-ph.GA2026
Classification of blazars based on data-driven approaches
Simone Vaccaro, Maria Isabel Carnerero, Claudia M. Raiteri +5
Active galactic nuclei (AGNs), including blazars, exhibit distinctive variability in their optical light curves, making them ideal for classification studies. This work uses data f…