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Under preparation. |
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# SNNs | ||
Tutorials and implementations for "Self-normalizing networks" | ||
# SelfNormalizingNetworks | ||
Tutorials and implementations for "Self-normalizing networks"(SNNs) as suggested by Klambauer et al. (2017). | ||
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## Versions | ||
- Tutorials: Python 3.5. and Tensorflow 1.1. | ||
- Basic python functions: Python 3.5. and Tensorflow 1.1. | ||
- Other: Python 3.5. and Tensorflow 0.11 | ||
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## Tutorials | ||
- Multilayer Perceptron ([notebook](https://github.com/bioinf-jku/SelfNormalizingNetworks/blob/master/SelfNormalizingNetworks_MLP_MNIST.ipynb)) | ||
- Convolutional Neural Network ([notebook](https://github.com/bioinf-jku/SelfNormalizingNetworks/blob/master/SelfNormalizingNetworks_CNN_MNIST.ipynb)) | ||
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## Design novel SELU functions | ||
- How to obtain the SELU parameters alpha and lambda for arbitrary fixed points ([notebook](https://github.com/bioinf-jku/SelfNormalizingNetworks/blob/master/getSELUparameters.ipynb)) | ||
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## Basic python functions to implement SNNs | ||
are provided as code chunks here: [selu.py](https://github.com/bioinf-jku/SelfNormalizingNetworks/blob/master/selu.py) | ||
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## Experiments on UCI, Tox21 and HTRU2 data sets | ||
Under preparation. |
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