Learning Gaia: A Generative Model Trained on the Gaia Data Release 3 Source Catalog

arXiv:2609.38326 · astro-ph.GA · Submitted 2026-09-29 · Read on arXiv

astro-ph.GA

Submitted: 2026-09-29

Updated: 2026-09-29

Terminology

• Foundation Model — 6× in this paper · explained in 3 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Core — 3× in this paper · explained in 2 episodes
• Downstream Tasks — 3× in this paper · explained in 2 episodes
• Flow Matching — 3× in this paper · explained in 8 episodes
• Foundation Models — 3× in this paper · explained in 7 episodes
• Generative Model — 3× in this paper · explained in 2 episodes
• Loss Function — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Color Magnitude Diagram — 1× in this paper
• Degeneracy — 1× in this paper · explained in 3 episodes
• European Space Agency — 1× in this paper
• Flow Matching Model — 1× in this paper · explained in 2 episodes
• Tests of Accuracy with Random Points — 1× in this paper
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Layer Normalization
• Galactic archaeology meets exoplanets: linking stellar birth radii to exoplanet demographics
• Via Machinae 3.0: A search for stellar streams in Gaia with the CATHODE algorithm
• Gaussian Error Linear Units (GELUs)
• Adam: A Method for Stochastic Optimization
• SpectraFM: Tuning into Stellar Foundation Models
• Sampling-Based Accuracy Testing of Posterior Estimators for General Inference
• Flow Matching for Generative Modeling
• Decoupled Weight Decay Regularization
• AION-1: Omnimodal Foundation Model for Astronomical Sciences
• PyTorch: An Imperative Style, High-Performance Deep Learning Library
• CFMI: Flow Matching for Missing Data Imputation
• AstroPT: Scaling Large Observation Models for Astronomy
• Score-Based Generative Modeling through Stochastic Differential Equations
• Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains
• Improving and generalizing flow-based generative models with minibatch optimal transport
• A Generalist Model Including Evolved Star Mass and Age

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