deep-kernel-transfer
heinsen_tree
deep-kernel-transfer | heinsen_tree | |
---|---|---|
1 | 2 | |
190 | 12 | |
1.6% | - | |
10.0 | 10.0 | |
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
heinsen_tree
What are some alternatives?
FSL-Mate - FSL-Mate: A collection of resources for few-shot learning (FSL).
jukebox - Code for the paper "Jukebox: A Generative Model for Music"
ipme - An interactive visualization tool that transforms probabilistic programming models into an "Interactive Probabilistic Models Explorer".
ALAE - [CVPR2020] Adversarial Latent Autoencoders
fortuna - A Library for Uncertainty Quantification.
wavegrad - A fast, high-quality neural vocoder.
rcps - Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"
diffwave - DiffWave is a fast, high-quality neural vocoder and waveform synthesizer.
MLBox - MLBox is a powerful Automated Machine Learning python library.
rtdl - Research on Tabular Deep Learning (Python package & papers) [Moved to: https://github.com/Yura52/rtdl]
Genome - Genome Network Ala Neural Network