3 papers
astro-ph.GA2025
Can AI Dream of Unseen Galaxies? Conditional Diffusion Model for Galaxy Morphology Augmentation
Chenrui Ma, Zechang Sun, Tao Jing +4
Observational astronomy relies on visual feature identification to detect critical astrophysical phenomena. While machine learning (ML) increasingly automates this process, models…
astro-ph.GA2025
Mapping Dust Attenuation at Kiloparsec Scales. II. Attenuation Curves from Near-Ultraviolet to Near-Infrared
Ruonan Guo, Cheng Li, Shuang Zhou +3
This is the second paper in a series that utilize IFS from MaNGA, NUV imaging from Swift/UVOT and NIR imaging from 2MASS to study dust attenuation properties on kpc scales in nearb…
astro-ph.IM2024
Regression for Astronomical Data with Realistic Distributions, Errors and Non-linearity
Tao Jing, Cheng Li
We have developed a new regression technique, the maximum likelihood (ML)-based method and its variant, the KS-test based method, designed to obtain unbiased regression results fro…