lincc-frameworks/hyrax
Hyrax - A low-code framework for rapid experimentation with ML & unsupervised discovery in astronomy
This framework helps astronomers quickly set up and run machine learning experiments for discovering new phenomena or classifying astronomical objects. It takes various forms of astronomical data (images, spectra, time-series) and applies machine learning models to identify patterns or categorize findings, allowing you to focus on interpreting scientific results. It is designed for astronomers and astrophysicists who use machine learning in their research.
Available on PyPI.
Use this if you are an astronomer who wants to rapidly experiment with different machine learning models on your astronomical data without getting bogged down in repetitive coding for project setup.
Not ideal if you are a developer looking for a general-purpose machine learning library outside of astronomical applications or if your models cannot be implemented in PyTorch.
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Language
Python
License
MIT
Category
Last pushed
Mar 12, 2026
Commits (30d)
0
Dependencies
32
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