Search Results - Massimo Brescia

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  1. 61
    Astroinformatics based search for globular clusters in the Fornax Deep Survey

    Astroinformatics based search for globular clusters in the Fornax Deep Survey by Angora, Giuseppe, Brescia, Massimo, Cavuoti, Stefano, Paolillo, Maurizio, Longo, Giuseppe, Cantiello, Michele, Capaccioli, Massimo, D'Abrusco, Raffaele, D'Ago, Giuseppe, Hilker, Michael, Iodice, Enrica, Mieske, Steffen, Napolitano, Nicola, Reynier Peletier, Pota, Vincenzo, Puzia, Thomas, Riccio, Giuseppe, Spavone, Marilena

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  2. 62
    The LSST-DESC 3x2pt Tomography Optimization Challenge

    The LSST-DESC 3x2pt Tomography Optimization Challenge by Zuntz, Joe, Lanusse, François, Malz, Alex I, Wright, Angus H, Slosar, Anže, Abolfathi, Bela, Alonso, David, Bault, Abby, Bom, Clécio R, Brescia, Massimo, Broussard, Adam, Jean-Eric Campagne, Cavuoti, Stefano, Cypriano, Eduardo S, Fraga, Bernardo M O, Gawiser, Eric, Gonzalez, Elizabeth J, Green, Dylan, Hatfield, Peter, Iyer, Kartheik, Kirkby, David, Andrina Nicola, Nourbakhsh, Erfan, Park, Andy, Teixeira, Gabriel, Heitmann, Katrin, Kovacs, Eve, Yao-Yuan, Mao, the LSST Dark Energy Science Collaboration

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  3. 63
    Probability density estimation of photometric redshifts based on machine learning

    Probability density estimation of photometric redshifts based on machine learning by Cavuoti, Stefano, Brescia, Massimo, Amaro, Valeria, Vellucci, Civita, Longo, Giuseppe, Tortora, Crescenzo

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  4. 64
    METAPHOR: Probability density estimation for machine learning based photometric redshifts

    METAPHOR: Probability density estimation for machine learning based photometric redshifts by Amaro, Valeria, Cavuoti, Stefano, Brescia, Massimo, Vellucci, Civita, Tortora, Crescenzo, Longo, Giuseppe

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  5. 65
    C3, A Command-line Catalogue Cross-match tool for large astrophysical catalogues

    C3, A Command-line Catalogue Cross-match tool for large astrophysical catalogues by Riccio, Giuseppe, Brescia, Massimo, Cavuoti, Stefano, Mercurio, Amata, di Giorgio, Anna Maria, Molinari, Sergio

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  6. 66
    METAPHOR: A machine learning based method for the probability density estimation of photometric redshifts

    METAPHOR: A machine learning based method for the probability density estimation of photometric redshifts by Cavuoti, Stefano, Amaro, Valeria, Brescia, Massimo, Vellucci, Civita, Tortora, Crescenzo, Longo, Giuseppe

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  7. 67
    Building the largest spectroscopic sample of ultra-compact massive galaxies with the Kilo Degree Survey

    Building the largest spectroscopic sample of ultra-compact massive galaxies with the Kilo Degree Survey by Scognamiglio, Diana, Tortora, Crescenzo, Spavone, Marilena, Spiniello, Chiara, Napolitano, Nicola R, D'Ago, Giuseppe, Francesco La Barbera, Getman, Fedor, Nivya Roy, Raj, Maria Angela, Radovich, Mario, Brescia, Massimo, Cavuoti, Stefano, Koopmans, Leon V E, Kuijken, Koen H, Longo, Giuseppe, Petrillo, Carlo Enrico

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  8. 68
    Weak Lensing Study in VOICE Survey I: Shear Measurement

    Weak Lensing Study in VOICE Survey I: Shear Measurement by Fu, Liping, Liu, Dezi, Radovich, Mario, Liu, Xiangkun, Pan, Chuzhong, Fan, Zuhui, Covone, Giovanni, Vaccari, Mattia, Amaro, Valeria, Brescia, Massimo, Capaccioli, Massimo, De Cicco, Demetra, Grado, Aniello, Limatola, Luca, Miller, Lance, Napolitano, Nicola R, Paolillo, Maurizio, Pignata, Giuliano

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  9. 69
    Cooperative photometric redshift estimation

    Cooperative photometric redshift estimation by Cavuoti, Stefano, Tortora, Crescenzo, Brescia, Massimo, Longo, Giuseppe, Radovich, Mario, Napolitano, Nicola R, Amaro, Valeria, Vellucci, Civita

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  10. 70
    An analysis of feature relevance in the classification of astronomical transients with machine learning methods

    An analysis of feature relevance in the classification of astronomical transients with machine learning methods by D'Isanto, Antonio, Cavuoti, Stefano, Brescia, Massimo, Donalek, Ciro, Longo, Giuseppe, Riccio, Giuseppe, Djorgovski, Stanislav G

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  11. 71
    Statistical analysis of probability density functions for photometric redshifts through the KiDS-ESO-DR3 galaxies

    Statistical analysis of probability density functions for photometric redshifts through the KiDS-ESO-DR3 galaxies by Amaro, Valeria, Cavuoti, Stefano, Brescia, Massimo, Vellucci, Civita, Longo, Giuseppe, Bilicki, Maciej, Jelte T A de Jong, Tortora, Crescenzo, Radovich, Mario, Napolitano, Nicola R, Buddelmeijer, Hugo

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  12. 72
    Photometric classification of emission line galaxies with Machine Learning methods

    Photometric classification of emission line galaxies with Machine Learning methods by Cavuoti, Stefano, Brescia, Massimo, D'Abrusco, Raffaele, Longo, Giuseppe, Paolillo, Maurizio

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  13. 73
    Photometric redshift estimation based on data mining with PhotoRApToR

    Photometric redshift estimation based on data mining with PhotoRApToR by Cavuoti, Stefano, Brescia, Massimo, Virgilio De Stefano, Longo, Giuseppe

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  14. 74
    Stellar formation rates in galaxies using Machine Learning models

    Stellar formation rates in galaxies using Machine Learning models by Michele Delli Veneri, Cavuoti, Stefano, Brescia, Massimo, Riccio, Giuseppe, Longo, Giuseppe

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  15. 75
    A cooperative approach among methods for photometric redshifts estimation: an application to KiDS data

    A cooperative approach among methods for photometric redshifts estimation: an application to KiDS data by Cavuoti, Stefano, Tortora, Crescenzo, Brescia, Massimo, Longo, Giuseppe, Radovich, Mario, Napolitano, Nicola R, Amaro, Valeria, Vellucci, Civita, Francesco La Barbera, Getman, Fedor, Grado, Aniello

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  16. 76
    Machine learning based data mining for Milky Way filamentary structures reconstruction

    Machine learning based data mining for Milky Way filamentary structures reconstruction by Riccio, Giuseppe, Cavuoti, Stefano, Schisano, Eugenio, Brescia, Massimo, Mercurio, Amata, Elia, Davide, Benedettini, Milena, Pezzuto, Stefano, Molinari, Sergio, Di Giorgio, Anna Maria

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  17. 77
    Photometric redshifts with Quasi Newton Algorithm (MLPQNA). Results in the PHAT1 contest

    Photometric redshifts with Quasi Newton Algorithm (MLPQNA). Results in the PHAT1 contest by Cavuoti, Stefano, Brescia, Massimo, Longo, Giuseppe, Mercurio, Amata

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  18. 78
    Data-Rich Astronomy: Mining Sky Surveys with PhotoRApToR

    Data-Rich Astronomy: Mining Sky Surveys with PhotoRApToR by Cavuoti, Stefano, Brescia, Massimo, Longo, Giuseppe

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  19. 79
    PhotoRaptor - Photometric Research Application To Redshifts

    PhotoRaptor - Photometric Research Application To Redshifts by Cavuoti, Stefano, Brescia, Massimo, Virgilio De Stefano, Longo, Giuseppe

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  20. 80
    Astrophysical Data Analytics based on Neural Gas Models, using the Classification of Globular Clusters as Playground

    Astrophysical Data Analytics based on Neural Gas Models, using the Classification of Globular Clusters as Playground by Angora, Giuseppe, Brescia, Massimo, Riccio, Giuseppe, Cavuoti, Stefano, Paolillo, Maurizio, Puzia, Thomas H

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