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The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Quasar Survey: Quasar Properties from Data Releases 6 to 9
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K. J. Luken, R. P. Norris, X. R. Wang, L. A. F. Park, Y. Guo and M. D. Filipović Publications of the Astronomical Society of Australia 40 (2023) https://doi.org/10.1017/pasa.2023.39
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Predicting the Redshift of Gamma-Ray Loud AGNs Using Supervised Machine Learning. II
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Identifications of RR Lyrae Stars and Quasars from the Simulated Data of Mephisto-W Survey
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The optical luminosity function of LOFAR radio-selected quasars at 1.4 ≤ z ≤ 5.0 in the NDWFS-Boötes field
SuperRAENN: A Semisupervised Supernova Photometric Classification Pipeline Trained on Pan-STARRS1 Medium-Deep Survey Supernovae
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Deep learning for strong lensing search: tests of the convolutional neural networks and new candidates from KiDS DR3
A Comparison of Photometric Redshift Techniques for Large Radio Surveys
Ray P. Norris, M. Salvato, G. Longo, et al. Publications of the Astronomical Society of the Pacific 131(1004) 108004 (2019) https://doi.org/10.1088/1538-3873/ab0f7b
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Preliminary Results of Using k-nearest-neighbor Regression to Estimate the Redshift of Radio-selected Data Sets
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PELICAN: deeP architecturE for the LIght Curve ANalysis