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Disentangling stellar atmospheric parameters in astronomical spectra using generative adversarial neural networks
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COSMIC: A Galaxy Cluster–Finding Algorithm Using Machine Learning
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The JWST Emission Line Survey (JELS): an untargeted search for H α emission line galaxies at z > 6 and their physical properties
C A Pirie, P N Best, K J Duncan, D J McLeod, R K Cochrane, M Clausen, J S Dunlop, S R Flury, J E Geach, C L Hale, E Ibar, R Kondapally, Zefeng Li, J Matthee, R J McLure, L Ossa-Fuentes, A L Patrick, Ian Smail, D Sobral, H M O Stephenson, J P Stott and A M Swinbank Monthly Notices of the Royal Astronomical Society 541(2) 1348 (2025) https://doi.org/10.1093/mnras/staf1006
The CatSouth Quasar Candidate Catalog for the Southern Sky and a Unified All-sky Catalog Based on Gaia DR3
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Machine Learning Classification of COSMOS2020 Galaxies: Quiescent versus Star-forming
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Improved source classification and performance analysis using Gaia DR3
Quaia, the Gaia-unWISE Quasar Catalog: An All-sky Spectroscopic Quasar Sample
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Search for and Study of the Brightest Stars in the Galaxy IC 342
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Exploring the dependence of gas cooling and heating functions on the incident radiation field with machine learning
David Robinson, Camille Avestruz and Nickolay Y Gnedin Monthly Notices of the Royal Astronomical Society 528(1) 255 (2024) https://doi.org/10.1093/mnras/stad3880
Boost recall in quasi-stellar object selection from highly imbalanced photometric datasets
Giorgio Calderone, Francesco Guarneri, Matteo Porru, Stefano Cristiani, Andrea Grazian, Luciano Nicastro, Manuela Bischetti, Konstantina Boutsia, Guido Cupani, Valentina D’Odorico, Chiara Feruglio and Fabio Fontanot Astronomy & Astrophysics 683 A34 (2024) https://doi.org/10.1051/0004-6361/202346625
Search of nearby resolved neutron stars among optical sources