Presentation for paper "Single Image Super-Resolution Based on Capsule Neural Networks"
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Updated
Apr 9, 2024 - Vue
Presentation for paper "Single Image Super-Resolution Based on Capsule Neural Networks"
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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 TensorFlow implementation of "Matrix Capsules with EM Routing" by Hinton et al. (2018).
A lightweight, human-scale, extensible content framework for the small web
Stacked Capsule Autoencoders (SCAE) in PyTorch and their semantic interpretation
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
PyTorch implementation of NIPS 2017 paper Dynamic Routing Between Capsules
A PyTorch Implementation of Matrix Capsules with EM Routing
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
Matrix Capsules experiment on German Traffic Sign Recognition Benchmark (GTSRB)
A tensorflow implemention of CapsNet in Geoffrey Hinton's paper Dynamic Routing Between Capsules
Implementation of Hinton's "Dynamic Routing Between Capsules" paper
easy definition of tensor flow based neural networks
Another implementation of Hinton's capsule networks in tensorflow.
A tensorflow implementation of Hinton's [matrix capsules with EM routing](https://openreview.net/pdf?id=HJWLfGWRb)
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