/SNNs

Tutorials and implementations for "Self-normalizing networks"

Primary LanguageJupyter NotebookGNU General Public License v3.0GPL-3.0

Self-Normalizing Networks

Tutorials and implementations for "Self-normalizing networks"(SNNs) as suggested by Klambauer et al. (arXiv pre-print).

Versions

  • Python 3.5 and Tensorflow 1.1

Tutorials

  • Multilayer Perceptron (notebook)
  • Convolutional Neural Network on MNIST (notebook)
  • Convolutional Neural Network on CIFAR10 (notebook)

Design novel SELU functions

  • How to obtain the SELU parameters alpha and lambda for arbitrary fixed points (notebook)

Basic python functions to implement SNNs

are provided as code chunks here: selu.py

Notebooks and code to produce Figure 1

are provided here: Figure1

Calculations and numeric checks of the theorems (Mathematica)

are provided as mathematica notebooks here:

UCI, Tox21 and HTRU2 data sets