Image de couverture de livre

Competing with AI Scientists: Agent-Driven Approach to Astrophysics Research

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Borrett, Thomas, Xu, Licong, Nilipour, Andy, Bolliet, Boris, Pierre, Sebastien, Allys, Erwan, Lecat, Celia, Dai, Biwei, Chang, Po-Wen, Bhimji, Wahid
Format:	Preprint
Publié:	2026
Sujets:	Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

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

Evaluating Retrieval-Augmented Generation Agents for Autonomous Scientific Discovery in Astrophysics
par: Xu, Xueqing, et autres
Publié: (2025)

Bayesian imaging inverse problem with scattering transform
par: Pierre, Sébastien, et autres
Publié: (2026)

OmniMol: Transferring Particle Physics Knowledge to Molecular Dynamics with Point-Edge Transformers
par: Elsharkawy, Ibrahim, et autres
Publié: (2026)

Discriminative versus Generative Approaches to Simulation-based Inference
par: Sluijter, Benjamin, et autres
Publié: (2025)

OmniLearned: A Foundation Model Framework for All Tasks Involving Jet Physics
par: Bhimji, Wahid, et autres
Publié: (2025)

cosmocnc: A fast, flexible, and accurate galaxy cluster number count likelihood code for cosmology
par: Zubeldia, Íñigo, et autres
Publié: (2024)

Wavelet Based Statistics for Enhanced 21cm EoR Parameter Constraints
par: Hothi, Ian, et autres
Publié: (2023)

Generative Models of 21cm EoR Lightcones with 3D Scattering Transforms
par: Hothi, Ian, et autres
Publié: (2025)

Astro-COLIBRI: Empowering Citizen Scientists in Multi-Messenger Astrophysics
par: Schüssler, Fabian, et autres
Publié: (2025)

FAIR Universe Weak Lensing ML Uncertainty Challenge: Handling Uncertainties and Distribution Shifts for Precision Cosmology
par: Dai, Biwei, et autres
Publié: (2026)

AI CFD Scientist: Toward Open-Ended Computational Fluid Dynamics Discovery with Physics-Aware AI Agents
par: Somasekharan, Nithin, et autres
Publié: (2026)

Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior
par: Subramanian, Shashank, et autres
Publié: (2023)

Enhancing Agentic Autonomous Scientific Discovery with Vision-Language Model Capabilities
par: Gandhi, Kahaan, et autres
Publié: (2025)

Cosmological inference from combining Planck and ACT cluster counts
par: Lee, Eunseong, et autres
Publié: (2024)

Comparing the morphology of molecular clouds without supervision
par: Richard, Pablo, et autres
Publié: (2024)

Scattering Spectra Models for Physics
par: Cheng, Sihao, et autres
Publié: (2023)

CLAPP: The CLASS LLM Agent for Pair Programming
par: Casas, Santiago, et autres
Publié: (2025)

Nemesis: A Multi-Scale, Multi-Physics Algorithm for Astrophysics
par: Hochart, Erwan, et autres
Publié: (2026)

EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery
par: Lyu, Yougang, et autres
Publié: (2026)

Untangling dust emission and CIB anisotropies with the Scattering Transform Statistics
par: Sinha, Srijita, et autres
Publié: (2026)

Deep learning the sources of MJO predictability: a spectral view of learned features
par: Yao, Lin, et autres
Publié: (2025)

Multiscale Flow for Robust and Optimal Cosmological Analysis
par: Dai, Biwei, et autres
Publié: (2023)

Insight into Faculty Open Access Perceptions: A Quantitative Analysis among UAE Faculty
par: Jeniece Tyria Lusk, et autres
Publié: (2023)

AiraXiv: An AI-Driven Open-Access Platform for Human and AI Scientists
par: Pan, Junshu, et autres
Publié: (2026)

When Robot Meets the God: Exploring the Relationship between Religion and AI
par: Soleh Hasan Wahid
Publié: (2025)

Separation of polarized dust emission in Planck observations with Scattering Transforms
par: Tsouros, Alexandros, et autres
Publié: (2026)

Extracting cosmological information from the abundance of galaxy clusters with simulation-based inference
par: Zubeldia, Íñigo, et autres
Publié: (2025)

LLM Agents as Social Scientists: A Human-AI Collaborative Platform for Social Science Automation
par: Wang, Lei, et autres
Publié: (2026)

The AI Data Scientist
par: Akimov, Farkhad, et autres
Publié: (2025)

Multiscale Turbulence Synthesis: Validation in 2D Hydrodynamics
par: Lesaffre, Pierre, et autres
Publié: (2025)

Comprehensive Performance Modeling and System Design Insights for Foundation Models
par: Subramanian, Shashank, et autres
Publié: (2024)

Rethinking the AI Scientist: Interactive Multi-Agent Workflows for Scientific Discovery
par: Weidener, Lukas, et autres
Publié: (2026)

AI Urban Scientist: Multi-Agent Collaborative Automation for Urban Research
par: Xia, Tong, et autres
Publié: (2025)

Superintelligent Agents Pose Catastrophic Risks: Can Scientist AI Offer a Safer Path?
par: Bengio, Yoshua, et autres
Publié: (2025)

ReplicationBench: Can AI Agents Replicate Astrophysics Research Papers?
par: Ye, Christine, et autres
Publié: (2025)

A Statistical Theory of Contrastive Learning via Approximate Sufficient Statistics
par: Lin, Licong, et autres
Publié: (2025)

Plug-in Performative Optimization
par: Lin, Licong, et autres
Publié: (2023)

Multi-Agent System for Cosmological Parameter Analysis
par: Laverick, Andrew, et autres
Publié: (2024)

A Survey of AI Scientists
par: Tie, Guiyao, et autres
Publié: (2025)