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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 51–75 of 395 papers

TitleStatusHype
Clustering via torque balance with mass and distance—0
Analysis of the HiSCORE Simulated Events in TAIGA Experiment Using Convolutional Neural Networks—0
Astronomical Images Quality Assessment with Automated Machine Learning—0
GBC: An Efficient and Adaptive Clustering Algorithm Based on Granular-Ball—0
Disentangling Dense Embeddings with Sparse Autoencoders—0
Clustering with phylogenetic tools in astrophysics—0
Astronomical Pipeline Provenance: A Use Case Evaluation—0
Astronomical source finding services for the CIRASA visual analytic platform—0
An Effective Semi-supervised Divisive Clustering Algorithm—0
Astronomia ex machina: a history, primer, and outlook on neural networks in astronomy—0
AstroSpy: On detecting Fake Images in Astronomy via Joint Image-Spectral Representations—0
AstroVisBench: A Code Benchmark for Scientific Computing and Visualization in Astronomy—0
Astro-NER -- Astronomy Named Entity Recognition: Is GPT a Good Domain Expert Annotator?—0
Algorithms and Statistical Models for Scientific Discovery in the Petabyte Era—0
ASTROMLSKIT: A New Statistical Machine Learning Toolkit: A Platform for Data Analytics in Astronomy—0
AstroMLab 4: Benchmark-Topping Performance in Astronomy Q&A with a 70B-Parameter Domain-Specialized Reasoning Model—0
A General Framework for Density Based Time Series Clustering Exploiting a Novel Admissible Pruning Strategy—0
Rethinking Irregular Time Series Forecasting: A Simple yet Effective Baseline—0
AstroMLab 2: AstroLLaMA-2-70B Model and Benchmarking Specialised LLMs for Astronomy—0
AstroMLab 1: Who Wins Astronomy Jeopardy!?—0
A General Approach to Domain Adaptation with Applications in Astronomy—0
Advancing RFI-Detection in Radio Astronomy with Liquid State Machines—0
AstroMAE: Redshift Prediction Using a Masked Autoencoder with a Novel Fine-Tuning Architecture—0
A comparative study of NeuralODE and Universal ODE approaches to solving Chandrasekhar White Dwarf equation—0
AstroLLaMA: Towards Specialized Foundation Models in Astronomy—0
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