deep-kernel-transfer
fortuna
| deep-kernel-transfer | fortuna | |
|---|---|---|
| 1 | 5 | |
| 190 | 855 | |
| 1.6% | 1.9% | |
| 10.0 | 8.2 | |
| over 2 years ago | 19 days ago | |
| Python | Python | |
| - | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
deep-kernel-transfer
-
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
fortuna
- 🚀 AWS launches Fortuna, an open-source library for Uncertainty Quantification
-
[P] 🚀 AWS launches Fortuna, an open-source library for Uncertainty Quantification
What is the best end-to-end example showing it? https://github.com/awslabs/fortuna/blob/main/examples/mnist_classification.ipynb ? It would be nice to have some visual explainer, as in https://github.com/aangelopoulos/conformal_classification .
- AWS Fortuna, an open-source library for Uncertainty Quantification
What are some alternatives?
FSL-Mate - FSL-Mate: A collection of resources for few-shot learning (FSL).
surface_normal_uncertainty - (ICCV 2021 - oral) Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation
ipme - An interactive visualization tool that transforms probabilistic programming models into an "Interactive Probabilistic Models Explorer".
uq-vae - Solving Bayesian Inverse Problems via Variational Autoencoders
rcps - Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"
pytorch-forecasting - Time series forecasting with PyTorch
MLBox - MLBox is a powerful Automated Machine Learning python library.
jax-resnet - Implementations and checkpoints for ResNet, Wide ResNet, ResNeXt, ResNet-D, and ResNeSt in JAX (Flax).
heinsen_tree - Reference implementation of "Tree Methods for Hierarchical Classification in Parallel" (Heinsen, 2022) in PyTorch.
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).