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Due to the flexibility of gpCAM, multi-task learning follows the logic of a non-stationary kernel. Here we show how multi-task learning can be accomplished in gpCAM and how a deep kernel can be set up to help. Of course, they are useful for single-task learning as well.
Due to the flexibility of gpCAM, multi-task learning follows the logic of a non-stationary kernel. Here we show how multi-task learning can be accomplished in gpCAM and how a deep kernel can be set up to help. Of course, they are useful for single-task learning as well.
The data can be downloaded here.
Always refer to the docs for the latest version of the example scripts.
Run the notebook here.
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