Browsing by Author "Evrard, A. E."

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    • Transfer learning for galaxy morphology from one survey to another 

      Sánchez, H. Domínguez; Huertas-Company, M.; Bernardi, M.; Kaviraj, S.; Fischer, J. L.; Abbott, T. M. C.; Abdalla, F. B.; Annis, J.; Avila, S.; Buckley-Geer, E.; Rosell, A. Carnero; Kind, M. Carrasco; Carretero, J.; Cunha, C. E.; D'Andrea, C. B.; Costa, L. N. da; Davis, C.; Vicente, J. De; Doel, P.; Evrard, A. E.; Fosalba, P.; Frieman, J.; García-Bellido, J.; Gaztanaga, E.; Gerdes, D. W.; Gruen, D.; Gruendl, R. A.; Gschwend, J.; Gutierrez, G.; Hartley, W. G.; Hollowood, D. L.; Honscheid, K.; Hoyle, B.; Kuehn, K.; Kuropatkin, N.; Lahav, O.; Maia, M. A. G.; March, M.; Melchior, P.; Menanteau, F.; Miquel, R.; Nord, B.; Plazas, A. A.; Sanchez, E.; Scarpine, V.; Schindler, R.; Schubnell, M.; Soares-Santos, M.; Sobreira, F.; Suchyta, E.; Swanson, M. E. C.; Tarle, G.; Walker, A. R.; Zuntz, J. (2018-12-28)
      Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of ...