7 citations · 8 across the 2 of their papers we have counts for
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astro-ph.GA2026
VAR-PZnn: A machine-learning framework for AGN photometric redshifts using color and variability-based features
S. Satheesh-Sheeba, P. Sánchez-Sáez, R. J. Assef +39
Photometric redshift estimation for active galactic nuclei (AGNs) remains a fundamental challenge for current and upcoming large-scale photometric surveys. Traditional spectral ene…
astro-ph.GA2024★ 7 cited
The Success of Optical Variability in Uncovering AGNs in Low-stellar Mass Galaxies
S. Bernal, P. Sánchez-Sáez, P. Arévalo +3
We used random forest algorithms to classify all objects in a large portion of the sky, using optical light curves obtained, or built from images provided, by the Zwicky Transient…