14 citations · 29 across the 10 of their papers we have counts for
5 papers · 1 filter
From Observation to Ground Truth: Reconstruction Losses of Galaxy Imaging Under Heteroscedastic Noise
Renhao Ye, Shiyin Shen, Quanfeng Xu
Deep learning is widely used to analyze galaxy images, and the reconstruction loss determines which image features a model prioritizes during training. Mean squared error (MSE) and…
From Galaxy Zoo DECaLS to BASS/MzLS: detailed galaxy morphology classification with unsupervised domain adaption
Renhao Ye, Shiyin Shen, Rafael S. de Souza +6
The DESI Legacy Imaging Surveys (DESI-LIS) comprise three distinct surveys: the Dark Energy Camera Legacy Survey (DECaLS), the Beijing-Arizona Sky Survey (BASS), and the Mayall z-b…
Galmoss: A package for GPU-accelerated Galaxy Profile Fitting
Mi Chen, Rafael S. de Souza, Quanfeng Xu +5
We introduce galmoss, a python-based, torch-powered tool for two-dimensional fitting of galaxy profiles. By seamlessly enabling GPU parallelization, galmoss meets the high computat…
Spatially resolved self-consistent spectral modelling of jellyfish galaxies from MUSE with FADO: trends with mass and stripping intensity
Gabriel M. Azevedo, Ana L. Chies-Santos, Rogério Riffel +5
We present a spatially resolved stellar population analysis of 61 jellyfish galaxies and 47 control galaxies observed with ESO/MUSE attempting to understand the general trends of t…
From Images to Features: Unbiased Morphology Classification via Variational Auto-Encoders and Domain Adaptation
Quanfeng Xu, Shiyin Shen, Rafael S. de Souza +7
We present a novel approach for the dimensionality reduction of galaxy images by leveraging a combination of variational auto-encoders (VAE) and domain adaptation (DA). We demonstr…