Photometric redshifts for the Kilo-Degree Survey: Machine-learning analysis with artificial neural networks

M. Bilicki, H. Hoekstra, M. J.I. Brown, V. Amaro, C. Blake, S. Cavuoti, J. T.A. De Jong, C. Georgiou, H. Hildebrandt, C. Wolf, A. Amon, M. Brescia, S. Brough, M. V. Costa-Duarte, T. Erben, K. Glazebrook, A. Grado, C. Heymans, T. Jarrett, S. JoudakiK. Kuijken, G. Longo, N. Napolitano, D. Parkinson, C. Vellucci, G. A. Verdoes Kleijn, L. Wang

Research output: Contribution to journalArticlepeer-review

64 Scopus citations

Fingerprint

Dive into the research topics of 'Photometric redshifts for the Kilo-Degree Survey: Machine-learning analysis with artificial neural networks'. Together they form a unique fingerprint.

Keyphrases

Physics