458 Open source projects that are alternatives of or similar to Capsule Net Pytorch

Official Pytorch code for (AAAI 2020) paper "Capsule Routing via Variational Bayes", https://arxiv.org/pdf/1905.11455.pdf

A Tensorflow implementation of CapsNet(Capsules Net) apply on german traffic sign dataset

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.

CapsLayer: An advanced library for capsule theory

Another implementation of Hinton's capsule networks in tensorflow.

🎆 A visualization of the CapsNet layers to better understand how it works

Code for my Master thesis on "Capsule Architecture as a Discriminator in Generative Adversarial Networks".

A Keras implementation of CapsNet in NIPS2017 paper "Dynamic Routing Between Capsules". Now test error ＝ 0.34%.

Empirical studies on Capsule Network representation and improvements implemented with PyTorch.

A Tensorflow implementation of CapsNet(Capsules Net) in paper Dynamic Routing Between Capsules

A curated list of awesome resources related to capsule networks

This repository contains the code of LiviaNET, a 3D fully convolutional neural network that was employed in our work: "3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study"

Various CNN models for CIFAR10 with Chainer

Computational Cognitive Neuroscience, Fourth Edition

Machine Learning for High Energy Physics.

A powerful and intuitive WYSIWYG interface that allows anyone to create Machine Learning models!

Lacmus is a cross-platform application that helps to find people who are lost in the forest using computer vision and neural networks.

A tool for automatic phoneme transcription

Tools and libraries to run neural networks in Minecraft ⛏

A PyTorch implementation of CapsNet based on NIPS 2017 paper "Dynamic Routing Between Capsules"

FastText for Node.js

Javascript/WebAssembly deep learning library for MLPs and convolutional neural networks

KitNET is a lightweight online anomaly detection algorithm, which uses an ensemble of autoencoders.

👷‍♂️ A simple package for extracting useful features from character objects 👷‍♀️

Easily craft fast Neural Networks on iOS! Use TensorFlow models. Metal under the hood.

Machine Learning for Flappy Bird using Neural Network and Genetic Algorithm

Unity Machine Learning Agents Toolkit

An easy-to-use interface for measuring uncertainty and robustness.

Example projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.

🛠 All-in-one web-based IDE specialized for machine learning and data science.

Discovering Neural Wirings (https://arxiv.org/abs/1906.00586)

EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis (official repository)

RObust document image BINarization

Machine Learning inference engine for Microcontrollers and Embedded devices

Efficient Spiking Neural Network framework, built on top of PyTorch for GPU acceleration

A collection of common algorithms and data structures implemented in java, c++, and python.

JeVois smart machine vision framework

Probabilistic time series modeling in Python

A lightweight contextual bandit & reinforcement learning library designed to be used in production Python services.

A High-Quality PyTorch Implementation of "Globally and Locally Consistent Image Completion".

Gradient Origin Networks - a new type of generative model that is able to quickly learn a latent representation without an encoder

Implementation of the paper "Adversarial Attacks on Neural Networks for Graph Data".

🐰 Python lib for remo - the app for annotations and images management in Computer Vision

A collection of deep learning models implemented in PyTorch

Deep Learning for Astronomers with Tensorflow

it's a small library for running trained Keras 2 models from a native C++ code.

Deep Learning for Julia

A P300 online spelling mechanism for Emotiv headsets. It's completely written in Node.js, and the GUI is based on Electron and Vue.

ASR with PyTorch

This repository contains the code of HyperDenseNet, a hyper-densely connected CNN to segment medical images in multi-modal image scenarios.

Python Adaptive Signal Processing

Implementation of simple autoencoders networks with Keras

Machine reading comprehension on clinical case reports

CryptoNets is a demonstration of the use of Neural-Networks over data encrypted with Homomorphic Encryption. Homomorphic Encryptions allow performing operations such as addition and multiplication over data while it is encrypted. Therefore, it allows keeping data private while outsourcing computation (see here and here for more about Homomorphic Encryptions and its applications). This project demonstrates the use of Homomorphic Encryption for outsourcing neural-network predictions. The scenario in mind is a provider that would like to provide Prediction as a Service (PaaS) but the data for which predictions are needed may be private. This may be the case in fields such as health or finance. By using CryptoNets, the user of the service can encrypt their data using Homomorphic Encryption and send only the encrypted message to the service provider. Since Homomorphic Encryptions allow the provider to operate on the data while it is encrypted, the provider can make predictions using a pre-trained Neural-Network while the data remains encrypted throughout the process and finaly send the prediction to the user who can decrypt the results. During the process the service provider does not learn anything about the data that was used, the prediction that was made or any intermediate result since everything is encrypted throughout the process. This project uses the Simple Encrypted Arithmetic Library SEAL version 3.2.1 implementation of Homomorphic Encryption developed in Microsoft Research.

Julia port of the Python autograd package.

PaddlePaddle End-to-End Development Toolkit（『飞桨』深度学习全流程开发工具）

A tool for retrosynthetic planning

A collection of Natural language processing pre-trained models.

Pytorch implementation of Block Neural Autoregressive Flow

Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.