☕ Brewing coffee pods without the hassle of complex machinery.
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Jun 28, 2024
☕ Brewing coffee pods without the hassle of complex machinery.
🚀🔍 Search platform for SpaceX complex physical items
easy definition of tensor flow based neural networks
Matrix Capsules experiment on German Traffic Sign Recognition Benchmark (GTSRB)
Implementation of Hinton's "Dynamic Routing Between Capsules" paper
Presentation for paper "Single Image Super-Resolution Based on Capsule Neural Networks"
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 tensorflow implemention of CapsNet in Geoffrey Hinton's paper Dynamic Routing Between Capsules
A lightweight, human-scale, extensible content framework for the small web
Stacked Capsule Autoencoders (SCAE) in PyTorch and their semantic interpretation
Another implementation of Hinton's capsule networks in tensorflow.
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
A tensorflow implementation for CapsNet
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).
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