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Extreme variability quasars from the Sloan Digital Sky Survey and the Dark Energy Survey, , , , , , , , , and 42 other author(s). (2017)cite arxiv:1706.07875Comment: submitted to ApJ; comments welcome.Galaxy Zoo: Reproducing Galaxy Morphologies via Machine Learning, , , , , , , , , and 3 other author(s). Monthly Notices of the Royal Astronomical Society, 406 (1): 342--353 (2010)The BINGO Project V: Further steps in Component Separation and Bispectrum Analysis, , , , , , , , , and 12 other author(s). (2021)cite arxiv:2107.01637Comment: 19 pages, 16 figures, 1 table. Submitted to A&A.The BINGO Project VII: Cosmological Forecasts from 21-cm Intensity Mapping, , , , , , , , , and 10 other author(s). (2021)cite arxiv:2107.01639Comment: 20 pages, 16 figures, 9 tables. Submitted to A&A.Dictionary Learning for Photometric Redshift Estimation., , , , , and . EUSIPCO, page 1740-1744. IEEE, (2018)Galaxy Zoo: Reproducing Galaxy Morphologies Via Machine Learning, , , , , , , , , and 3 other author(s). (2009)cite arxiv:0908.2033Comment: 13 Pages, 5 figures, 10 tables. Accepted for publication in MNRAS. Revised to match accepted version..Foreground removal and 21 cm signal estimates: comparing different blind methods for the BINGO Telescope, , , , , , , , , and 8 other author(s). (2022)cite arxiv:2209.11701.Crowdsourcing quality control for Dark Energy Survey images., , , , , , , , , and 40 other author(s). Astron. Comput., (2016)Convolutional Neural Networks for Spectroscopic Redshift Estimation on Euclid Data., , , , , and . IEEE Trans. Big Data, 6 (3): 460-476 (2020)Denoising galaxy spectra with coupled dictionary learning., , , , and . EUSIPCO, page 498-502. IEEE, (2017)