The assignments for the Neural Networks for Machine Learning from Prof. Hinton
-
Updated
Jan 4, 2017 - MATLAB
The assignments for the Neural Networks for Machine Learning from Prof. Hinton
Pyhton notebook based on: Programming assignment 3 from Hinton's Neural Networks course from coursera https://www.coursera.org/learn/neural-networks
A Tensorflow implementation of CapsNet(Capsules Net) in Hinton's paper Dynamic Routing Between Capsules
MXNet implementation of CapsNet
MXNet implementation of CapsNet
A simple tensorflow implementation of CapsNet (by Dr. G. Hinton), based on my understanding. This repository is built with an aim to simplify the concept, implement and understand it.
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.
A Tensorflow implementation of CapsNet(Capsules Net) in Hinton's paper Dynamic Routing Between Capsules
CapsNet for NLP
The code implements Hinton's matrix capsule with em routing for Cifar-10 dataset
Empirical studies on Capsule Network representation and improvements implemented with PyTorch.
Programming Assignments for the Neural Networks for Machine Learning Course on Coursera
[NO MAINTENANCE INTENDED] A PyTorch implementation of CapsNet architecture in the NIPS 2017 paper "Dynamic Routing Between Capsules".
CapsNet models
A PyTorch implementation of Matrix Capsules with EM Routing by Hinton et al.
Neural Networks for Machine Learning(Spring'17) - Hinton
Simple implementation of the standard Boltzmann Machine model with MATLAB
PyTorch implementation of (Hinton) Knowledge Distillation and a base class for simple implementation of other distillation methods.
Add a description, image, and links to the hinton topic page so that developers can more easily learn about it.
To associate your repository with the hinton topic, visit your repo's landing page and select "manage topics."