December 15, 2017 article Open access Deep learning approach for classifying, detecting and predicting photometric redshifts of quasars in the Sloan Digital Sky Survey stripe 82 Astronomy and Astrophysics DOI: 10.1051/0004-6361/201731106 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 5 stored of 68 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Deep Learning Voigt Profiles. I. Single-Cloud Doublets 2024 The Astronomical Journal article Physics and Astronomy Galaxies: Formation, Evolution, Phenomena Open access 3 citations The PAU Survey and Euclid: Improving broadband photometric redshifts with multi-task learning 2023 Astronomy and Astrophysics article Physics and Astronomy Galaxies: Formation, Evolution, Phenomena Open access 12 citations Finding Quasars behind the Galactic Plane. I. Candidate Selections with Transfer Learning 2021 The Astrophysical Journal Supplement Series article Physics and Astronomy Galaxies: Formation, Evolution, Phenomena Open access 34 citations Photometric selection and redshifts for quasars in the Kilo-Degree Survey Data Release 4 2021 Astronomy and Astrophysics article Physics and Astronomy Galaxies: Formation, Evolution, Phenomena Open access 40 citations The optical luminosity function of LOFAR radio-selected quasars at 1.4 ≤z≤ 5.0 in the NDWFS-Boötes field 2020 Astronomy and Astrophysics article Physics and Astronomy Galaxies: Formation, Evolution, Phenomena Open access 5 citations 5 results References 0