A Tensorflow implementation of the How Can We Be So Dense? The Benefits of Using Highly Sparse Representations.
This code was tested using TF2.0 and python 3.6.
pip install -r requirements.txt
This code only implement the simple CNN architectures SparseCNN1 and DenseCNN1
To test other architectures, you can modify the sparse_net.py
or dense_net.py
To launch training SparseCNN1 as described in the paper
python train_evaluate.py
As described in the paper, the sparseCNN shows more robustness to white noise in the inputs.