GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning

Gaussian processes (GPs) are non-parametric, flexible models that work well in many tasks. Combining GPs with deep learning methods via deep kernel learning (DKL) is especially compelling due to the strong representational power induced by the network.

Data and Resources

Cite this as

Idan Achituve, Aviv Navon, Yochai Yemini, Gal Chechik, Ethan Fetaya (2024). Dataset: GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning. https://doi.org/10.57702/mti4vxep

DOI retrieved: December 2, 2024

Additional Info

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Created December 2, 2024
Last update December 2, 2024
Author Idan Achituve
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Aviv Navon
Yochai Yemini
Gal Chechik
Ethan Fetaya
Homepage https://github.com/IdanAchituve/GP-Tree