Image de couverture de livre

SuperCode: Sustainability PER AI-driven CO-DEsign

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Broekema, P. Chris, van Nieuwpoort, Rob V.
Format:	Preprint
Publié:	2024
Sujets:	Instrumentation and Methods for Astrophysics Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Energy and polarization based on-line interference mitigation in radio interferometry
par: Yatawatta, Sarod, et autres
Publié: (2024)

AI Agents for Ground-Based Gamma Astronomy
par: Kostunin, D., et autres
Publié: (2025)

Quantum Radio Astronomy: Data Encodings and Quantum Image Processing
par: Brunet, Thomas, et autres
Publié: (2023)

AstroReview: An LLM-driven Multi-Agent Framework for Telescope Proposal Peer Review and Refinement
par: Wang, Yutong, et autres
Publié: (2025)

AI in Space for Scientific Missions: Strategies for Minimizing Neural-Network Model Upload
par: Ekelund, Jonah, et autres
Publié: (2024)

On-Orbit Space AI: Federated, Multi-Agent, and Collaborative Algorithms for Satellite Constellations
par: Wang, Ziyang
Publié: (2026)

Open Science and Artificial Intelligence for supporting the sustainability of the SRC Network: The espSRC case
par: Garrido, J., et autres
Publié: (2025)

Beyond AI as Assistants: Toward Autonomous Discovery in Cosmology
par: Xu, Licong, et autres
Publié: (2026)

Solar synthetic imaging: Introducing denoising diffusion probabilistic models on SDO/AIA data
par: Ramunno, Francesco P., et autres
Publié: (2024)

AstroM$^3$: A self-supervised multimodal model for astronomy
par: Rizhko, Mariia, et autres
Publié: (2024)

Fine-tuning LLMs for Autonomous Spacecraft Control: A Case Study Using Kerbal Space Program
par: Carrasco, Alejandro, et autres
Publié: (2024)

Preliminary Report on Mantis Shrimp: a Multi-Survey Computer Vision Photometric Redshift Model
par: Engel, Andrew, et autres
Publié: (2024)

Unsupervised Machine Learning for the Classification of Astrophysical X-ray Sources
par: Pérez-Díaz, Víctor Samuel, et autres
Publié: (2024)

Using Galaxy Evolution as Source of Physics-Based Ground Truth for Generative Models
par: Li, Yun Qi, et autres
Publié: (2024)

Leveraging Deep Learning for Time Series Extrinsic Regression in predicting photometric metallicity of Fundamental-mode RR Lyrae Stars
par: Monti, Lorenzo, et autres
Publié: (2024)

What is the Role of Large Language Models in the Evolution of Astronomy Research?
par: Fouesneau, Morgan, et autres
Publié: (2024)

Temporal Stamp Classifier: Classifying Short Sequences of Astronomical Alerts
par: O., Daniel Neira, et autres
Publié: (2024)

Mantis Shrimp: Exploring Photometric Band Utilization in Computer Vision Networks for Photometric Redshift Estimation
par: Engel, Andrew, et autres
Publié: (2025)

AstroCompress: A benchmark dataset for multi-purpose compression of astronomical data
par: Truong, Tuan, et autres
Publié: (2025)

AstroMMBench: A Benchmark for Evaluating Multimodal Large Language Models Capabilities in Astronomy
par: Shi, Jinghang, et autres
Publié: (2025)

Plausible but Wrong: A case study on Agentic Failures in Astrophysical Workflows
par: Rawat, Shivam, et autres
Publié: (2026)

AstroAlertBench: Evaluating the Accuracy, Reasoning, and Honesty of Multimodal LLMs in Astronomical Classification
par: Chen, Claire, et autres
Publié: (2026)

MARVEL: A Multi Agent-based Research Validator and Enabler using Large Language Models
par: Mukund, Nikhil, et autres
Publié: (2026)

Explainable machine learning workflows for radio astronomical data processing
par: Yatawatta, S., et autres
Publié: (2026)

SM-Net: Learning a Continuous Spectral Manifold from Multiple Stellar Libraries
par: Anwar, Omar, et autres
Publié: (2026)

InferA: A Smart Assistant for Cosmological Ensemble Data
par: Tam, Justin Z., et autres
Publié: (2025)

Solving Online Resource-Constrained Scheduling for Follow-Up Observation in Astronomy: a Reinforcement Learning Approach
par: Zhang, Yajie, et autres
Publié: (2025)

Convolutional Autoencoders for Data Compression and Anomaly Detection in Small Satellite Technologies
par: Jayeprokash, Dishanand, et autres
Publié: (2025)

Category-based Galaxy Image Generation via Diffusion Models
par: Fan, Xingzhong, et autres
Publié: (2025)

Natural Language-Driven Global Mapping of Martian Landforms
par: Wang, Yiran, et autres
Publié: (2026)

A Semi-Supervised Learning Method for the Identification of Bad Exposures in Large Imaging Surveys
par: Luo, Yufeng, et autres
Publié: (2025)

Cosmo3DFlow: Wavelet Flow Matching for Spatial-to-Spectral Compression in Reconstructing the Early Universe
par: Islam, Md. Khairul, et autres
Publié: (2026)

Enhancing the development of Cherenkov Telescope Array control software with Large Language Models
par: Kostunin, Dmitriy, et autres
Publié: (2025)

Radio Astronomy in the Era of Vision-Language Models: Prompt Sensitivity and Adaptation
par: Drozdova, Mariia, et autres
Publié: (2025)

OmniSpectra: A Unified Foundation Model for Native Resolution Astronomical Spectra
par: Islam, Md Khairul, et autres
Publié: (2026)

Fried Parameter Estimation from Single Wavefront Sensor Image with Artificial Neural Networks
par: Smith, Jeffrey, et autres
Publié: (2025)

Anomaly detection in radio galaxy data with trainable COSFIRE filters
par: Ndung'u, Steven, et autres
Publié: (2025)

Machines Learn to Infer Stellar Parameters Just by Looking at a Large Number of Spectra
par: Sedaghat, Nima, et autres
Publié: (2020)

FRTSearch: Unified Detection and Parameter Inference of Fast Radio Transients using Instance Segmentation
par: Zhang, Bin, et autres
Publié: (2026)

What Understanding Means in AI-Laden Astronomy
par: Ting, Yuan-Sen, et autres
Publié: (2026)