3 papers
astro-ph.IM2025
Interpreting deep learning-based stellar mass estimation via causal analysis and mutual information decomposition
Wei Zhang, Qiufan Lin, Yuan-Sen Ting +4
End-to-end deep learning models fed with multi-band galaxy images are powerful data-driven tools used to estimate galaxy physical properties in the absence of spectroscopy. However…
astro-ph.IM2025
Investigation on deep learning-based galaxy image translation models
Hengxin Ruan, Qiufan Lin, Shupei Chen +2
Galaxy image translation is an important application in galaxy physics and cosmology. With deep learning-based generative models, image translation has been performed for image gen…
astro-ph.IM2024
CLAP. I. Resolving miscalibration for deep learning-based galaxy photometric redshift estimation
Qiufan Lin, Hengxin Ruan, Dominique Fouchez +6
Obtaining well-calibrated photometric redshift probability densities for galaxies without a spectroscopic measurement remains a challenge. Deep learning discriminative models, typi…