chaht01/Co2L
Co^2L: Contrastive Continual Learning (ICCV2021)
This is a machine learning framework for training AI models that need to learn new information continuously without forgetting what they already know. It takes in sequential datasets, like images or sensor data arriving over time, and produces a robust model that retains knowledge across different learning stages. This is designed for AI researchers and machine learning engineers developing adaptive systems.
100 stars. No commits in the last 6 months.
Use this if you are developing AI models that must adapt to new data over time, performing well on current tasks while preserving performance on past tasks.
Not ideal if your model only needs to be trained once on a fixed dataset and doesn't require continuous learning or adaptation.
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100
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24
Language
Python
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Last pushed
Mar 30, 2022
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