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Mapping the Galaxy Color-Redshift Relation: Optimal Photometric Redshift Calibration Strategies for Cosmology Surveys, , , , , , , , , and 10 other author(s). (2015)cite arxiv:1509.03318Comment: ApJ accepted, 17 pages, 10 figures.Machine learning based data mining for Milky Way filamentary structures reconstruction., , , , , , , , , and . CoRR, (2015)Neural Gas Based Classification of Globular Clusters., , , , , and . DAMDID/RCDL (Selected Papers), volume 822 of Communications in Computer and Information Science, page 86-101. Springer, (2017)METAPHOR: Probability density estimation for machine learning based photometric redshifts., , , , , and . Astroinformatics, volume 12 of Proceedings of the International Astronomical Union, page 197-200. Cambridge University Press, (2016)A novel approach to the classification of terrestrial drainage networks based on deep learning and preliminary results on Solar System bodies., , , , , and . CoRR, (2021)DAME: A Web Oriented Infrastructure for Scientific Data Mining & Exploration, , , , , , , , , and 5 other author(s). CoRR, (2010)C3: A Command-line Catalogue Cross-matching tool for modern astrophysical survey data., , , , , and . Astroinformatics, volume 12 of Proceedings of the International Astronomical Union, page 327-332. Cambridge University Press, (2016)VIALACTEA science gateway for Milky Way analysis., , , , , , , , , and 6 other author(s). Future Gener. Comput. Syst., (2019)ULISSE: A Tool for One-shot Sky Exploration and its Application to Active Galactic Nuclei Detection., , , , , , , and . CoRR, (2022)Euclid: Identification of asteroid streaks in simulated images using deep learning., , , , , , , , , and 32 other author(s). CoRR, (2023)