9 papers
Estimating Uncertainty in Galaxy Morphology Classification
Kai Cheng, Ruoqi Wang, Qiong Luo
Astronomers classify galaxy morphology to investigate cosmic evolution. While deep foundation models are increasingly utilized in Galaxy Morphology Classification (GMC), little wor…
Improving Radio Interferometry Imaging by Explicitly Modeling Cross-Domain Consistency in Reconstruction
Kai Cheng, Ruoqi Wang, Qiong Luo
Radio astronomy plays a crucial role in understanding the universe, particularly within the realm of non-thermal astrophysics. Images of celestial objects are derived from the sign…
VVTRec: Radio Interferometric Reconstruction through Visual and Textual Modality Enrichment
Kai Cheng, Ruoqi Wang, Qiong Luo
Radio astronomy is an indispensable discipline for observing distant celestial objects. Measurements of wave signals from radio telescopes, called visibility, need to be transforme…
D-GAP: Improving Out-of-Domain Robustness via Dataset-Agnostic and Gradient-Guided Augmentation in Frequency and Pixel Spaces
Ruoqi Wang, Haitao Wang, Shaojie Guo +1
Out-of-domain (OOD) robustness is challenging to achieve in real-world computer vision, especially in unsupervised domain adaptation scenarios, where shifts in image background, st…
Improving Out-of-Domain Robustness with Targeted Augmentation in Frequency and Pixel Spaces
Ruoqi Wang, Haitao Wang, Shaojie Guo +1
Out-of-domain (OOD) robustness under domain adaptation settings, where labeled source data and unlabeled target data come from different distributions, is a key challenge in real-w…
GalaxAlign: Mimicking Citizen Scientists' Multimodal Guidance for Galaxy Morphology Analysis
Ruoqi Wang, Haitao Wang, Qiong Luo
Galaxy morphology analysis involves studying galaxies based on their shapes and structures. For such studies, fundamental tasks include identifying and classifying galaxies in astr…
VisRec: A Semi-Supervised Approach to Radio Interferometric Data Reconstruction
Ruoqi Wang, Haitao Wang, Qiong Luo +2
Radio telescopes produce visibility data about celestial objects, but these data are sparse and noisy. As a result, images created on raw visibility data are of low quality. Recent…
PolarRec: Radio Interferometric Data Reconstruction with Polar Coordinate Representation
Ruoqi Wang, Zhuoyang Chen, Jiayi Zhu +2
In radio astronomy, visibility data, which are measurements of wave signals from radio telescopes, are transformed into images for observation of distant celestial objects. However…
A Conditional Denoising Diffusion Probabilistic Model for Radio Interferometric Image Reconstruction
Ruoqi Wang, Zhuoyang Chen, Qiong Luo +1
In radio astronomy, signals from radio telescopes are transformed into images of observed celestial objects, or sources. However, these images, called dirty images, contain real so…