Capsule network is a neural network architecture that embeds features as capsules and routes them with a voting mechanism to next layer of capsules.

Unlike in other implementations of models, we've included a sample, because it is difficult to understand some concepts with just the modules. This is the annotated code for a model that uses capsules to classify MNIST dataset

This file holds the implementations of the core modules of Capsule Networks.

I used jindongwang/Pytorch-CapsuleNet to clarify some confusions I had with the paper.

Here's a notebook for training a Capsule Network on MNIST dataset.