114 citations · 533 across the 17 of their papers we have counts for
3 papers · 1 filter
Inferring galaxy dark halo properties from visible matter with Machine Learning
Rodrigo von Marttens, Luciano Casarini, Nicola R. Napolitano +6
Next-generation surveys will provide photometric and spectroscopic data of millions to billions of galaxies with unprecedented precision. This offers a unique chance to improve our…
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…
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…