In the “Neural Networks” chapter of the PyTorch “60 Minute Blitz” tutorial, the final link in the example network (Yann LeCun’s LeNet) is described as a set of “Gaussian connections”. These are then implemented in torch in almost the same way as the two “Full connection” links, the only difference being that there is no ReLU activation function applied. Is this the only difference between a full connection and a Gaussian one? Or how does the lack of a ReLU imply that we end up with a layer of Gaussian connections?