xbresson/graph_convnets_pytorch

The code provides a simple example of graph ConvNets for the MNIST classification task. The graph is a 8-nearest neighbor graph of a 2D grid. The signals on graph are the MNIST images vectorized as $28 2 \times 1$ vectors. PyTorch has not yet implemented function torch.mm(sparse, It will be certainly implemented but in the meantime, I defined a new autograd function for sparse variables, called "my_sparse_mm", by subclassing torch.autograd.function