AI + Astronomy News
Efficient Regression Models for Scan Statistics
Exploring how dark matter can imprint itself of the assembly of galaxies
Exploring how interactive tools can help astronomers identify potentially incorrect labels and unusual patterns in large collections of radio astronomy data
Clustering spectral cubes from radio astronomy
Exploring why vision-language models hallucinate visual details of nonexistent objects to follow prompt-based information
Recovering high resolution information from blurred images crowded with stars
Developing a faster AI method for reconstructing the early universe from 3D maps of today’s cosmos
Applying machine-learning methods for scalable and validated radio astronomy data preparation and quality assurance
How the First Galaxies Ionized the Neutral Hydrogen at the Cosmic Scales
Making astronomical archives more accessible through AI: STABLE (Summer Team for Astronomical Benchmarking & LLM Engineering) highlights
“Vector Summary Pseudo Posteriors for Simulation-Based Inference with Applications to Cosmology” presented at the STAI-X conference at Harvard
CosmicAI Research, “Density-Informed Pseudo-Counts for Calibrated Evidential Deep Learning” selected for a paper award at STAI-X!
How Researchers Navigate Accountability, Transparency, and Trust When Using AI Tools in Research
Cosmic Horizons 2026: Uniting Astronomers and AI Experts at NSF NRAO
Unraveling the origins of Supermassive Black Holes using Cosmological Simulations
Learning the Universe at High Redshifts: Impact of Accretion Modeling on Early Black Hole Growth
CosmicAI Researchers explored how to build agentic systems for data science tasks critical to scientific discovery
Resolving galaxy formation in the early Universe with BonFIRE and CampFIRE
AI & Science: What Is the Future of Discovery?
