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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 251–300 of 395 papers

TitleStatusHype
Upper Mid-Band Spectrum for 6G: Vision, Opportunity and Challenges—0
Using a Conditional Generative Adversarial Network to Control the Statistical Characteristics of Generated Images for IACT Data Analysis—0
Using Large Language Models for Automated Grading of Student Writing about Science—0
Variational Inference for Gaussian Process Modulated Poisson Processes—0
Very Fast EM-based Mixture Model Clustering using Multiresolution kd-trees—0
WaveGNN: Modeling Irregular Multivariate Time Series for Accurate Predictions—0
WaveMo: Learning Wavefront Modulations to See Through Scattering—0
What is the Role of Large Language Models in the Evolution of Astronomy Research?—0
When Spectral Modeling Meets Convolutional Networks: A Method for Discovering Reionization-era Lensed Quasars in Multi-band Imaging Data—0
AstroLLaMA: Towards Specialized Foundation Models in Astronomy—0
ZCal: Machine learning methods for calibrating radio interferometric data—0
Invariant Discovery of Features Across Multiple Length Scales: Applications in Microscopy and Autonomous Materials Characterization—0
Disentangling Dense Embeddings with Sparse Autoencoders—0
pathfinder: A Semantic Framework for Literature Review and Knowledge Discovery in Astronomy—0
AI Agents for Ground-Based Gamma Astronomy—0
Rethinking Irregular Time Series Forecasting: A Simple yet Effective Baseline—0
5G Advanced: Wireless Channel Virtualization and Resource Mapping for Real Time Spectrum Sharing—0
A brief review of contrastive learning applied to astrophysics—0
A comparative study of NeuralODE and Universal ODE approaches to solving Chandrasekhar White Dwarf equation—0
Active Cost-aware Labeling of Streaming Data—0
Active Learning of Model Evidence Using Bayesian Quadrature—0
A deep learning framework for jointly extracting spectra and source-count distributions in astronomy—0
A Deep Neural Network Based Reverse Radio Spectrogram Search Algorithm—0
Advanced Image Processing for Astronomical Images—0
Advanced Single Image Resolution Upsurging Using a Generative Adversarial Network—0
Advances on the classification of radio image cubes—0
Advancing RFI-Detection in Radio Astronomy with Liquid State Machines—0
A General Approach to Domain Adaptation with Applications in Astronomy—0
A General Framework for Density Based Time Series Clustering Exploiting a Novel Admissible Pruning Strategy—0
Algorithms and Statistical Models for Scientific Discovery in the Petabyte Era—0
GBC: An Efficient and Adaptive Clustering Algorithm Based on Granular-Ball—0
Analysis of the HiSCORE Simulated Events in TAIGA Experiment Using Convolutional Neural Networks—0
An Effective Semi-supervised Divisive Clustering Algorithm—0
A New Approach for Image Authentication Framework for Media Forensics Purpose—0
An unsupervised approach towards promptable defect segmentation in laser-based additive manufacturing by Segment Anything—0
Applications of AI in Astronomy—0
A review of Generative Adversarial Networks (GANs) and its applications in a wide variety of disciplines -- From Medical to Remote Sensing—0
A review of unsupervised learning in astronomy—0
A Review on Digital Pixel Sensors—0
AstroClearNet: Deep image prior for multi-frame astronomical image restoration—0
AstroLLaMA-Chat: Scaling AstroLLaMA with Conversational and Diverse Datasets—0
AstroLLaVA: towards the unification of astronomical data and natural language—0
AstroM^3: A self-supervised multimodal model for astronomy—0
AstroMAE: Redshift Prediction Using a Masked Autoencoder with a Novel Fine-Tuning Architecture—0
AstroMLab 1: Who Wins Astronomy Jeopardy!?—0
AstroMLab 2: AstroLLaMA-2-70B Model and Benchmarking Specialised LLMs for Astronomy—0
AstroMLab 4: Benchmark-Topping Performance in Astronomy Q&A with a 70B-Parameter Domain-Specialized Reasoning Model—0
ASTROMLSKIT: A New Statistical Machine Learning Toolkit: A Platform for Data Analytics in Astronomy—0
Astro-NER -- Astronomy Named Entity Recognition: Is GPT a Good Domain Expert Annotator?—0
Astronomia ex machina: a history, primer, and outlook on neural networks in astronomy—0
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