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Astronomy

Astronomy is the study of everything in the universe beyond Earth’s atmosphere. That includes objects we can see with our naked eyes, like the Sun, the Moon, the planets, and the stars. It also contains objects we can only see with telescopes or other instruments, like faraway galaxies and tiny particles. And it even includes questions about things we can't see, like dark matter and energy.

Papers

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Showing 251–275 of 395 papers

TitleStatusHype
Can semi-supervised learning reduce the amount of manual labelling required for effective radio galaxy morphology classification?Code0
E(2) Equivariant Self-Attention for Radio AstronomyCode0
Robustness of deep learning algorithms in astronomy -- galaxy morphology studies—0
Swift sky localization of gravitational waves using deep learning seeded importance samplingCode0
The diffusion of scientific terms – tracing individuals’ influence in the history of science for English—0
Photon-Limited Deblurring using Algorithm Unrolling—0
Self-supervised denoising for massive noisy images—0
Astronomical source finding services for the CIRASA visual analytic platform—0
On the Quality of Deep Representations for Kepler Light Curves Using Variational Auto-EncodersCode0
A New Approach for Image Authentication Framework for Media Forensics Purpose—0
A review of Generative Adversarial Networks (GANs) and its applications in a wide variety of disciplines -- From Medical to Remote Sensing—0
Astronomical Pipeline Provenance: A Use Case Evaluation—0
Data science and Machine learning in the Clouds: A Perspective for the Future—0
Noisy Labels for Weakly Supervised Gamma Hadron Classification—0
Compressed particle methods for expensive models with application in Astronomy and Remote Sensing—0
Autoencoder-driven Spiral Representation Learning for Gravitational Wave Surrogate Modelling—0
SpecGrav -- Detection of Gravitational Waves using Deep Learning—0
Partially Coherent Radar Unties Range Resolution from Bandwidth Limitations—0
PNet -- A Deep Learning Based Photometry and Astrometry Bayesian Framework—0
First Full-Event Reconstruction from Imaging Atmospheric Cherenkov Telescope Real Data with Deep Learning—0
Segmentation of high dimensional means over multi-dimensional change points and connections to regression trees—0
Prediction of soft proton intensities in the near-Earth space using machine learningCode0
Drifting Features: Detection and evaluation in the context of automatic RRLs identification in VVV—0
Morphological classification of astronomical images with limited labelling—0
Robust Feature Disentanglement in Imaging Data via Joint Invariant Variational Autoencoders: from Cards to Atoms—0
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