A tensorflow implementation for CapsNet
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Updated
Dec 4, 2017 - Python
A tensorflow implementation for CapsNet
A tensorflow implementation of Hinton's [matrix capsules with EM routing](https://openreview.net/pdf?id=HJWLfGWRb)
Another implementation of Hinton's capsule networks in tensorflow.
easy definition of tensor flow based neural networks
Implementation of Hinton's "Dynamic Routing Between Capsules" paper
A tensorflow implemention of CapsNet in Geoffrey Hinton's paper Dynamic Routing Between Capsules
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
A PyTorch Implementation of Matrix Capsules with EM Routing
PyTorch implementation of NIPS 2017 paper Dynamic Routing Between Capsules
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 lightweight, human-scale, extensible content framework for the small web
A TensorFlow implementation of "Matrix Capsules with EM Routing" by Hinton et al. (2018).
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.
🚀🔍 Search platform for SpaceX complex physical items
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