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Precise photometric redshifts with a narrow-band filter set: The PAU Survey at the William Herschel Telescope, , , , , и . (2014)cite arxiv:1402.3220Comment: Submitted to MNRAS. 19 pages, 18 figures, 6 tables.Discovery of a Candidate Binary Supermassive Black Hole in a Periodic Quasar from Circumbinary Accretion Variability, , , , , , , , , и 61 other автор(ы). (2020)cite arxiv:2008.12317Comment: resubmitted to MNRAS after addressing referee reports; comments are welcome.VDES J2325-5229 a z=2.7 gravitationally lensed quasar discovered using morphology independent supervised machine learning, , , , , , , , , и 49 other автор(ы). (2016)cite arxiv:1607.01391Comment: 11 pages, 7 figures, 7 tables, MNRAS submitted.Constraints on Decaying Dark Matter with DES-Y1 and external data, , , , , , , , , и 75 other автор(ы). (2020)cite arxiv:2011.04606Comment: 23 pages, 11 figures. DES extensions group.Machine Learning for Searching the Dark Energy Survey for Trans-Neptunian Objects., , , , , , , , , и 49 other автор(ы). CoRR, (2020)Dark Energy Survey Year 1 Results: Constraining Baryonic Physics in the Universe, , , , , , , , , и 67 other автор(ы). (2020)cite arxiv:2007.15026Comment: 24 pages, 18 figures, 2 tables. submitted to MNRAS. A brief video summary of this paper is available at https://www.youtube.com/watch?v=QbeNwk5papU.The PAU survey: Ly$\alpha$ intensity mapping forecast, , , , , , , , , и 2 other автор(ы). (2020)cite arxiv:2006.07177Comment: 18 pages, 14 figures, 4 tables. To be submitted to MNRAS.A machine learning approach to galaxy properties: Joint redshift - stellar mass probability distributions with Random Forest., , , , , , , , , и 63 other автор(ы). CoRR, (2020)Local primordial non-Gaussianity from the large-scale clustering of photometric DESI luminous red galaxies., , , , , , , , , и 38 other автор(ы). CoRR, (2023)Optical follow-up of gravitational wave triggers with DECam during the first two LIGO/VIRGO observing runs., , , , , , , , , и 74 other автор(ы). Astron. Comput., (2020)