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Efficient identification of broad absorption line quasars using dimensionality reduction and machine learning
Wei-Bo Kao, Yanxia Zhang and Xue-Bing Wu Publications of the Astronomical Society of Japan 76(4) 653 (2024) https://doi.org/10.1093/pasj/psae037
Transferring spectroscopic stellar labels to 217 million Gaia DR3 XP stars with SHBoost
A. Khalatyan, F. Anders, C. Chiappini, A. B. A. Queiroz, S. Nepal, M. dal Ponte, C. Jordi, G. Guiglion, M. Valentini, G. Torralba Elipe, M. Steinmetz, M. Pantaleoni-González, S. Malhotra, Ó. Jiménez-Arranz, H. Enke, L. Casamiquela and J. Ardèvol Astronomy & Astrophysics 691 A98 (2024) https://doi.org/10.1051/0004-6361/202451427
Cataclysmic variables from Sloan Digital Sky Survey – V (2020–2023) identified using machine learning
Keith Inight, Boris T Gänsicke, Axel Schwope, Scott F Anderson, Elmé Breedt, Joel R Brownstein, Sebastian Demasi, Susanne Friedrich, J J Hermes, Knox S Long, Timothy Mulvany, Gautham Adamane Pallathadka, Mara Salvato, Simone Scaringi, Matthias R Schreiber, Guy S Stringfellow, John R Thorstensen, Gagik Tovmassian and Nadia L Zakamska Monthly Notices of the Royal Astronomical Society 536(2) 1057 (2024) https://doi.org/10.1093/mnras/stae2524
White dwarf Random Forest classification through Gaia spectral coefficients
White dwarf spectral type-temperature distribution from Gaia DR3 and the Virtual Observatory
S. Torres, P. Cruz, R. Murillo-Ojeda, F. M. Jiménez-Esteban, A. Rebassa-Mansergas, E. Solano, M. E. Camisassa, R. Raddi and J. Doliguez Le Lourec Astronomy & Astrophysics 677 A159 (2023) https://doi.org/10.1051/0004-6361/202346977