This is a lightweight repository of bayesian neural network for PyTorch.
- torch 1.2.0
- python 3.6
pip install torchbnnorgit clone https://github.com/Harry24k/bayesian-neural-network-pytorch
import torchbnn- Bayesian Neural Network Regression (code): In this demo, two-layer bayesian neural network is constructed and trained on simple custom data. It shows how bayesian-neural-network works and randomness of the model.
- Bayesian Neural Network Classification (code): To classify Iris data, in this demo, two-layer bayesian neural network is constructed and trained on the Iris data. It shows how bayesian-neural-network works and randomness of the model.
- Convert to Bayesian Neural Network (code):
To convert a basic neural network to a bayesian neural network, this demo shows how
nonbayes_to_bayesandbayes_to_nonbayeswork. - Freeze Bayesian Neural Network (code):
To freeze a bayesian neural network, which means force a bayesian neural network to output same result for same input, this demo shows the effect of
freezeandunfreeze.
If you use this package, please cite the following BibTex (SemanticScholar, GoogleScholar):
@article{lee2022graddiv,
title={Graddiv: Adversarial robustness of randomized neural networks via gradient diversity regularization},
author={Lee, Sungyoon and Kim, Hoki and Lee, Jaewook},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
year={2022},
publisher={IEEE}
}
Here is update records of this package.
- @kumar-shridhar github:PyTorch-BayesianCNN
- @xuanqing94 github:BayesianDefense
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