3 papers
astro-ph.GA2025
Deciphering galaxy images using machine vision -- Combining variational autoencoder and principal component analysis for feature extraction
Samuel Howie, Ting-Yun Cheng, Carlton M. Baugh
Here, we present a machine vision approach, combining a VAE framework with PCA, to decipher galaxy images. Using mock gri-band images from the EAGLE simulation, the VAE finds that…
astro-ph.GA2025
Explaining JWST counts with galaxy formation models
Giorgio Manzoni, Tom Broadhurst, Jeremy Lim +18
A distinct power-law break is apparent m_AB approximately 21 in the deep Near-Infrared PEARLS-JWST galaxy counts. The break becomes more pronounced at longer wavelengths, with the…
astro-ph.IM2024
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…