activity
20172021
most citedSpectroscopic and Photometric Redshift Estimation by Neural Networks For the China Space Station Optical Survey (CSS-OS)

29 citations · 58 across the 3 of their papers we have counts for

collaborators

7 papers

astro-ph.IM202128 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…

astro-ph.CO202129 cited

Spectroscopic and Photometric Redshift Estimation by Neural Networks For the China Space Station Optical Survey (CSS-OS)

Xingchen Zhou, Yan Gong, Xian-Min Meng +6

The estimation of spectroscopic and photometric redshifts (spec-z and photo-z) is crucial for future cosmological surveys. It can directly affect several powerful measurements of t…

astro-ph.GA2020

Euclid preparation: X. The Euclid photometric-redshift challenge

Euclid Collaboration, G. Desprez, S. Paltani +170

Forthcoming large photometric surveys for cosmology require precise and accurate photometric redshift (photo-z) measurements for the success of their main science objectives. Howev…

astro-ph.IM2018

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

Valeria Amaro, Stefano Cavuoti, Massimo Brescia +8

Despite the high accuracy of photometric redshifts (zphot) derived using Machine Learning (ML) methods, the quantification of errors through reliable and accurate Probability Densi…

astro-ph.GA2018

Evolution of galaxy size--stellar mass relation from the Kilo Degree Survey

N. Roy, N. R. Napolitano, F. La Barbera +16

We have obtained structural parameters of about 340,000 galaxies from the Kilo Degree Survey (KiDS) in 153 square degrees of data release 1, 2 and 3. We have performed a seeing con…

astro-ph.IM2018

Data Deluge in Astrophysics: Photometric Redshifts as a Template Use Case

Massimo Brescia, Stefano Cavuoti, Valeria Amaro +4

Astronomy has entered the big data era and Machine Learning based methods have found widespread use in a large variety of astronomical applications. This is demonstrated by the rec…