66 citations · 133 across the 11 of their papers we have counts for
4 papers · 1 filter
The miniJPAS survey quasar selection III: Classification with artificial neural networks and hybridisation
G. Martínez-Solaeche, Carolina Queiroz, R. M. González Delgado +28
This paper is part of large effort within the J-PAS collaboration that aims to classify point-like sources in miniJPAS, which were observed in 60 optical bands over 1 deg$^2…
The miniJPAS survey quasar selection II: Machine learning classification with photometric measurements and uncertainties
Natália V. N. Rodrigues, L. Raul Abramo, Carolina Queiroz +23
Astrophysical surveys rely heavily on the classification of sources as stars, galaxies or quasars from multi-band photometry. Surveys in narrow-band filters allow for greater discr…
The miniJPAS survey quasar selection I: Mock catalogues for classification
Carolina Queiroz, L. Raul Abramo, Natália V. N. Rodrigues +27
In this series of papers, we employ several machine learning (ML) methods to classify the point-like sources from the miniJPAS catalogue, and identify quasar candidates. Since no r…
Mimicking the halo-galaxy connection using machine learning
Natalí S. M. de Santi, Natália V. N. Rodrigues, Antonio D. Montero-Dorta +3
Elucidating the connection between the properties of galaxies and the properties of their hosting haloes is a key element in galaxy formation. When the spatial distribution of obje…