5 citations · 5 across the 3 of their papers we have counts for
6 papers
Beyond traditional emission-line diagnostics: using autoencoders to uncover active galactic nuclei in DESI spectra
J. A. Alcolea, M. Siudek, M. Eriksen +49
The growing volume of spectroscopic data in modern surveys motivates data-driven approaches that complement traditional emission-line diagnostics for active galactic nuclei (AGN) i…
Euclid: Photometric redshift calibration with the clustering redshifts technique
W. d'Assignies, M. Manera, C. Padilla +172
Aims: The precision of cosmological constraints from imaging surveys hinges on accurately estimating the redshift distribution of tomographic bins, especially their mean r…
Joint probabilistic inference of galaxy redshifts and rest-frame spectra from photometric fluxes with latent diffusion
Han-Yue Guo, Martin Eriksen
Wide-field imaging surveys now provide photometry for billions of sources, while spectroscopic observations remain limited, motivating methods that can extract spectroscopic inform…
The PAU Survey: The -band galaxy luminosity function from the present-day to
S. Koonkor, C. M. Baugh, G. Manzoni +13
We present a measurement of the -band galaxy luminosity function from the present-day to , using over 1.1 million galaxies from the Physics of the Accelerating Universe S…
The PAU Survey: Measuring intrinsic galaxy alignments in deep wide fields as a function of colour, luminosity, stellar mass and redshift
D. Navarro-Gironés, M. Crocce, E. Gaztañaga +21
We present the measurements and constraints of intrinsic alignments (IA) in the Physics of the Accelerating Universe Survey (PAUS) deep wide fields, which include the W1 and W3 fie…
ANNZ+: an enhanced photometric redshift estimation algorithm with applications on the PAU Survey
Imdad Mahmud Pathi, John Y. H. Soo, Mao Jie Wee +16
ANNZ is a fast and simple algorithm which utilises artificial neural networks (ANNs), it was known as one of the pioneers of machine learning approaches to photometric redshift est…