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CLAP
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Statistical analysis of probability density functions for photometric redshifts through the KiDS-ESO-DR3 galaxies
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M Delli Veneri, S Cavuoti, M Brescia, G Longo and G Riccio Monthly Notices of the Royal Astronomical Society 486(1) 1377 (2019) https://doi.org/10.1093/mnras/stz856
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Data Analytics and Management in Data Intensive Domains
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Probing the sparse tails of redshift distributions with Voronoi tessellations
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Measuring photometric redshifts using galaxy images and Deep Neural Networks
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WISE × SuperCOSMOS PHOTOMETRIC REDSHIFT CATALOG: 20 MILLION GALAXIES OVER 3π STERADIANS
Maciej Bilicki, John A. Peacock, Thomas H. Jarrett, Michelle E. Cluver, Natasha Maddox, Michael J. I. Brown, Edward N. Taylor, Nigel C. Hambly, Aleksandra Solarz, Benne W. Holwerda, Ivan Baldry, Jon Loveday, Amanda Moffett, Andrew M. Hopkins, Simon P. Driver, Mehmet Alpaslan and Joss Bland-Hawthorn The Astrophysical Journal Supplement Series 225(1) 5 (2016) https://doi.org/10.3847/0067-0049/225/1/5
METAPHOR: Probability density estimation for machine learning based photometric redshifts
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Feature importance for machine learning redshifts applied to SDSS galaxies
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A. V. Meshcheryakov, V. V. Glazkova, S. V. Gerasimov, R. A. Burenin and G. A. Khorunzhev Astronomy Letters 41(7) 307 (2015) https://doi.org/10.1134/S1063773715070038
Photometric redshift estimation based on data mining with PhotoRApToR
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