gram-ai/capsule-networks
A PyTorch implementation of the CapsNet architecture for image classification using dynamic routing between capsules.

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This repository implements the CapsNet architecture from the 2017 paper by Sabour, Frosst, and Hinton. It trains a multi-layer capsule network on MNIST for digit recognition, using an iterative routing-by-agreement mechanism where lower-level capsules send outputs to higher-level capsules based on vector agreement. The implementation supports CUDA acceleration and uses TorchNet for training orchestration.