deep-kernel-transfer
rcps
| deep-kernel-transfer | rcps | |
|---|---|---|
| 1 | 1 | |
| 190 | 83 | |
| 1.6% | - | |
| 10.0 | 3.4 | |
| over 2 years ago | 3 months 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
rcps
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[R] Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification - Link to a free online lecture by the author in comments
​Distribution-Free, Risk-Controlling Prediction Sets https://arxiv.org/abs/2101.02703 https://github.com/aangelopoulos/rcps
What are some alternatives?
FSL-Mate - FSL-Mate: A collection of resources for few-shot learning (FSL).
conformal_classification - Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).
ipme - An interactive visualization tool that transforms probabilistic programming models into an "Interactive Probabilistic Models Explorer".
pytorch-forecasting - Time series forecasting with PyTorch
fortuna - A Library for Uncertainty Quantification.
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