14 citations · 18 across the 9 of their papers we have counts for
7 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 DESI to Euclid: A Generative Bridge to Improve Measurements of Galaxy Structure
Renhao Ye, Shiyin Shen
Ground-based seeing imprints size-dependent biases on galaxy structural parameters, yet the high-resolution space-based imaging needed to improve these measurements currently cover…
Schrödinger's Seed: Purr-fect Initialization for an Impurr-fect Universe
Mi chen, Renhao Ye
Context. Random seed selection in deep learning is often arbitrary -- conventionally fixed to values such as 42, a number with no known feline endorsement. Aims. We propose that ca…
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…
Capivara: A Spectral-based Segmentation Method for IFU Data Cubes
Rafael S. de Souza, Luis G. Dahmer-Hahn, Shiyin Shen +7
We present capivara, a fast and scalable spectral-based segmentation package designed to study astrophysical properties within distinct structural components of galaxies. This spec…
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…
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…