uiucsn/Astro-ORACLE
ORACLE - The first hierarchical deep-learning model for real-time, context-aware classification of the LSST alert stream
This project helps astronomers rapidly classify transient and variable objects observed by surveys like LSST. It takes photometric observations (light curves) and contextual information (like host galaxy redshift) and outputs high-confidence classifications of astronomical events, even with limited initial data. It's designed for astrophysicists and researchers analyzing real-time astronomical alert streams.
Use this if you need to quickly categorize new astrophysical events from large observational datasets, especially with a hierarchical classification system.
Not ideal if you are looking for a general-purpose machine learning library or if your classification needs are outside of transient and variable astrophysics.
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13
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1
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Oct 22, 2025
Commits (30d)
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