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PyTorch implementation of bayesian neural network [torchbnn]
| Date | Stars |
|---|---|
| 2026-07-31 | 561 |
| 2026-08-02 | 561 |
| 2026-08-03 | 561 |
| 2026-08-06 | 561 |
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# Bayesian-Neural-Network-Pytorch
<p>
<a href="https://github.com/Harry24k/adversarial-attacks-pytorch/blob/master/LICENSE"><img alt="MIT License" src="https://img.shields.io/github/license/Harry24k/bayesian-neural-network-pytorch" /></a>
<a href="https://img.shields.io/pypi/v/torchbnn"><img alt="Pypi" src="https://img.shields.io/pypi/v/torchbnn.svg" /></a>
<a href="https://bayesian-neural-network-pytorch.readthedocs.io/en/latest/"><img alt="Documentation Status" src="https://readthedocs.org/projects/bayesian-neural-network-pytorch/badge/?version=latest" /></a>
</p>
This is a lightweight repository of bayesian neural network for PyTorch.
## Usage
### :clipboard: Dependencies
- torch 1.2.0
- python 3.6
### :hammer: Installation
- `pip install torchbnn` or
- `git clone https://github.com/Harry24k/bayesian-neural-network-pytorch`
```python
import torchbnn
```
### :rocket: Demos
* **Bayesian Neural Network Regression** ([code](https://github.com/Harry24k/bayesian-neural-network-pytorch/blob/master/demos/Bayesian%20Neural%20Network%20Regression.ipynb)):
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](https://github.com/Harry24k/bayesian-neural-network-pytorch/blob/master/demos/Bayesian%20Neural%20Network%20Classification.ipynb)):
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](https://github.com/Harry24k/bayesian-neural-network-pytorch/blob/master/demos/Convert%20to%20Bayesian%20Neural%20Network.ipynb)):
To convert a basic neural network to a bayesian neural network, this demo shows how `nonbayes_to_bayes` and `bayes_to_nonbayes` work.
* **Freeze Bayesian Neural Network** ([code](https://github.com/Harry24k/bayesian-neural-network-pytorch/blob/master/demos/Freeze%20Bayesian%20Neural%20Network.ipynb)):
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 `freeze` and `unfreeze`.
## Citation
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}
}
```
## :mag_right: Update Records
Here is [update records](Update%20Records.md) of this package.
## Thanks to
* @kumar-shridhar [github:PyTorch-BayesianCNN](https://github.com/kumar-shridhar/PyTorch-BayesianCNN)
* @xuanqing94 [github:BayesianDefense](https://github.com/xuanqing94/BayesianDefense)
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matched fp:cc791c85e94c65af, topic:deep-learning, topic:neural-network, topic:pytorch