PyTorch implementation of NIPS 2017 paper Dynamic Routing Between Capsules

Reference implementation of "An Algorithm for Routing Vectors in Sequences" (Heinsen, 2022) and "An Algorithm for Routing Capsules in All Domains" (Heinsen, 2019), for composing deep neural networks.

A PyTorch Implementation of Matrix Capsules with EM Routing

A TensorFlow implementation of "Matrix Capsules with EM Routing" by Hinton et al. (2018).

A tensorflow implementation of Hinton's [matrix capsules with EM routing](https://openreview.net/pdf?id=HJWLfGWRb)

The code for "No Routing Needed Between Capsules". This repository contains the code used for the experiments detailed in a forthcoming paper. The paper is available pre-published at arXiv: http://arxiv.org/abs/2001.09136

Stacked Capsule Autoencoders (SCAE) in PyTorch and their semantic interpretation

A tensorflow implementation for CapsNet

Another implementation of Hinton's capsule networks in tensorflow.

Implementation of Hinton's "Dynamic Routing Between Capsules" paper

easy definition of tensor flow based neural networks

Matrix Capsules experiment on German Traffic Sign Recognition Benchmark (GTSRB)

Homogeneous Vector Capsules Enable Adaptive Gradient Descent in Convolutional Neural Networks. This repository contains the code used for the experiments detailed in a paper currently submitted to IEEE Transactions on Neural Networks and Learning Systems. The paper is available pre-published at arXiv: http://arxiv.org/abs/1906.08676

Models and examples built with TensorFlow

Models and examples built with TensorFlow

A tensorflow implemention of CapsNet in Geoffrey Hinton's paper Dynamic Routing Between Capsules