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‎README.md

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@@ -26,6 +26,20 @@ This is a lightweight repository of bayesian neural network for PyTorch.
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import torchbnn
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```
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### :rocket: Demos
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* **Bayesian Neural Network Regression** ([code](https://github.com/Harry24k/bayesian-neural-network-pytorch/blob/master/demos/Bayesian%20Neural%20Network%20Regression.ipynb)):
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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.
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* **Bayesian Neural Network Classification** ([code](https://github.com/Harry24k/bayesian-neural-network-pytorch/blob/master/demos/Bayesian%20Neural%20Network%20Classification.ipynb)):
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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.
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* **Convert to Bayesian Neural Network** ([code](https://github.com/Harry24k/bayesian-neural-network-pytorch/blob/master/demos/Convert%20to%20Bayesian%20Neural%20Network.ipynb)):
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To convert a basic neural network to a bayesian neural network, this demo shows how `nonbayes_to_bayes` and `bayes_to_nonbayes` work.
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* **Freeze Bayesian Neural Network** ([code](https://github.com/Harry24k/bayesian-neural-network-pytorch/blob/master/demos/Freeze%20Bayesian%20Neural%20Network.ipynb)):
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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`.
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## Citation
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If you use this package, please cite the following BibTex (SemanticScholar, GoogleScholar):
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Here is [update records](Update%20Records.md) of this package.
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## :rocket: Demos
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* **Bayesian Neural Network Regression** ([code](https://github.com/Harry24k/bayesian-neural-network-pytorch/blob/master/demos/Bayesian%20Neural%20Network%20Regression.ipynb)):
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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.
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* **Bayesian Neural Network Classification** ([code](https://github.com/Harry24k/bayesian-neural-network-pytorch/blob/master/demos/Bayesian%20Neural%20Network%20Classification.ipynb)):
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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.
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* **Convert to Bayesian Neural Network** ([code](https://github.com/Harry24k/bayesian-neural-network-pytorch/blob/master/demos/Convert%20to%20Bayesian%20Neural%20Network.ipynb)):
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To convert a basic neural network to a bayesian neural network, this demo shows how `nonbayes_to_bayes` and `bayes_to_nonbayes` work.
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* **Freeze Bayesian Neural Network** ([code](https://github.com/Harry24k/bayesian-neural-network-pytorch/blob/master/demos/Freeze%20Bayesian%20Neural%20Network.ipynb)):
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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`.
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## Thanks to
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* @kumar-shridhar [github:PyTorch-BayesianCNN](https://github.com/kumar-shridhar/PyTorch-BayesianCNN)

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