Volume Preserving Neural Networks

Implementation in PyTorch

A neural network architecture that is fully volume preserving including the coupled chebyshev volume preserving activation function.

This is the implementation of the paper:

G. MacDonald, A. Godbout, B. Gillcash, and S. Cairns. Volume Preserving Neural Networks: A Solution to the Vanishing Gradient Problem. (2019)

link to paper (arXix preprint): https://arxiv.org/abs/1911.09576

If you use this code, please cite (arXiv preprint):

@misc{macdonald2019volumepreserving,
    title={Volume-preserving Neural Networks: A Solution to the Vanishing Gradient Problem},
    author={Gordon MacDonald and Andrew Godbout and Bryn Gillcash and Stephanie Cairns},
    year={2019},
    eprint={1911.09576},
    archivePrefix={arXiv},
    primaryClass={cs.LG}
}

Getting Started

-demo_mnist jupyter notebook provides a demonstration of the VPNN on the MNIST dataset

Dependencies

- Torch 1.1.0
- torchvision 0.3.0
- matplotlib 3.1.1
- numpy 
- nltk 
- jupyter
- sklearn
- seaborn