30 citations · 63 across the 6 of their papers we have counts for
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astro-ph.IM2021★ 30 cited
Improving the reliability of photometric redshift with machine learning
Oleksandra Razim, Stefano Cavuoti, Massimo Brescia +3
In order to answer the open questions of modern cosmology and galaxy evolution theory, robust algorithms for calculating photometric redshifts (photo-z) for very large samples of g…
astro-ph.IM2021★ 28 cited
Photometric redshifts with machine learning, lights and shadows on a complex data science use case
Massimo Brescia, Stefano Cavuoti, Oleksandra Razim +3
The current role of data-driven science is constantly increasing its importance within Astrophysics, due to the huge amount of multi-wavelength data collected every day, characteri…