deep-kernel-transfer
ipme
deep-kernel-transfer | ipme | |
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1 | 1 | |
190 | 24 | |
1.6% | - | |
10.0 | 0.0 | |
over 2 years ago | over 1 year ago | |
Python | Python | |
- | MIT License |
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deep-kernel-transfer
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What approach to take predicting a simple data stream?
Interesting approach to small datasets. Here is an implementation I'll look at: https://github.com/BayesWatch/deep-kernel-transfer
ipme
What are some alternatives?
FSL-Mate - FSL-Mate: A collection of resources for few-shot learning (FSL).
EOmaps - A library to create interactive maps of geographical datasets
fortuna - A Library for Uncertainty Quantification.
uncertainty-toolbox - Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
rcps - Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"
surface_normal_uncertainty - (ICCV 2021 - oral) Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation
MLBox - MLBox is a powerful Automated Machine Learning python library.
heinsen_tree - Reference implementation of "Tree Methods for Hierarchical Classification in Parallel" (Heinsen, 2022) in PyTorch.
Genome - Genome Network Ala Neural Network