Photometric Redshift Estimation with Convolutional Neural Networks and Galaxy Images: A Case Study of Resolving Biases in Data-Driven Methods

no code implementations • 21 Feb 2022 • Q. Lin, D. Fouchez, J. Pasquet, M. Treyer, R. Ait Ouahmed, S. Arnouts, O. Ilbert

Deep Learning models have been increasingly exploited in astrophysical studies, yet such data-driven algorithms are prone to producing biased outputs detrimental for subsequent analyses.

Photometric Redshift Estimation Representation Learning