ShadeAlsha/ICon
ICLR 2025 - official implementation for "I-Con: A Unifying Framework for Representation Learning"
This project offers a unified way to design and implement various machine learning models that learn meaningful data representations. It takes raw data and, through a configuration, produces embeddings that capture underlying relationships. Data scientists and machine learning researchers can use this to quickly experiment with different representation learning algorithms.
127 stars.
Use this if you need to rapidly prototype and compare multiple representation learning algorithms for your data, or if you're developing new ones and want a flexible framework.
Not ideal if you are looking for an out-of-the-box solution with pre-trained models, rather than a framework for building and experimenting with algorithms.
Stars
127
Forks
14
Language
Jupyter Notebook
License
—
Category
Last pushed
Feb 18, 2026
Commits (30d)
0
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