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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 226–250 of 395 papers

TitleStatusHype
Poissonian Blurred Image Deconvolution by Framelet based Local Minimal Prior—0
GBC: An Efficient and Adaptive Clustering Algorithm Based on Granular-Ball—0
Overview of STEM Science as Process, Method, Material, and Data Named EntitiesCode0
Identifying outliers in astronomical images with unsupervised machine learning—0
DeepGraviLens: a Multi-Modal Architecture for Classifying Gravitational Lensing DataCode0
Une version polyatomique de l'algorithme Frank-Wolfe pour résoudre le problème LASSO en grandes dimensions—0
Data-driven Influence Based Clustering of Dynamical Systems—0
Identifying Exoplanets with Machine Learning Methods: A Preliminary Study—0
Computation of Optical Refractive Index Structure Parameter from its Statistical Definition Using Radiosonde Data—0
Identifying Transients in the Dark Energy Survey using Convolutional Neural NetworksCode0
Deep Residual Error and Bag-of-Tricks Learning for Gravitational Wave Surrogate ModelingCode0
Recursive Monte Carlo and Variational Inference with Auxiliary VariablesCode0
Determining Research Priorities for Astronomy Using Machine Learning—0
RRL:Regional Rotation Layer in Convolutional Neural Networks—0
Incorporating Texture Information into Dimensionality Reduction for High-Dimensional ImagesCode0
Optimal Transport for Super Resolution Applied to Astronomy Imaging—0
Performance Evaluation of Infrared Image Enhancement Techniques—0
Robust line-of-sight pointing control on-board a stratospheric balloon-borne platform—0
Analysis of the HiSCORE Simulated Events in TAIGA Experiment Using Convolutional Neural Networks—0
Real-time Detection of Anomalies in Multivariate Time Series of Astronomical Data—0
Mathematical Model of International Trade and Global Economy—0
Quantum Machine Learning for Radio Astronomy—0
Building astroBERT, a language model for Astronomy & Astrophysics—0
Learning Methods for Solving Astronomy Course Problems—0
Learning to learn STEM courses—0
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