143 Open source projects that are alternatives of or similar to Capsule Networks

TensorFlow2教程 TensorFlow 2.0 Tutorial 入门教程实战案例

Pytorch implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) for MNIST dataset

Google Street View House Number(SVHN) Dataset, and classifying them through CNN

Android TensorFlow MachineLearning MNIST Example (Building Model with TensorFlow for Android)

The origin of the Non-IID phenomenon is the personalization of users, who generate the Non-IID data. With Non-IID (Not Independent and Identically Distributed) issues existing in the federated learning setting, a myriad of approaches has been proposed to crack this hard nut. In contrast, the personalized federated learning may take the advantage…

GPU Accelerated t-SNE for CUDA with Python bindings

PyTorch Implementation of CycleGAN and SSGAN for Domain Transfer (Minimal)

A MNIST-like fashion product database. Benchmark 👇

Build deep learning applications in a new and easy way.

Early stopping for PyTorch

mnist with Tensorflow

An implementation for mnist center loss training and visualization

Tensorflow implementation of variational auto-encoder for MNIST

Comparison of Generative Models in Tensorflow

A free audio dataset of spoken digits. Think MNIST for audio.

Combine multiple MNIST digits to create datasets with 100/1000 classes for few-shot learning/meta-learning

[ISBI'21] MedMNIST Classification Decathlon: A Lightweight AutoML Benchmark for Medical Image Analysis

Tensorflow implementation of different GANs and their comparisions

Speech command recognition with capsule network & various NNs / KWS on Google Speech Command Dataset.

Deep generative models implemented with TensorFlow 2.0: eg. Restricted Boltzmann Machine (RBM), Deep Belief Network (DBN), Deep Boltzmann Machine (DBM), Convolutional Variational Auto-Encoder (CVAE), Convolutional Generative Adversarial Network (CGAN)

In this part, I've introduced and experimented with ways to interpret and evaluate models in the field of image. (Pytorch)

A repository for recording the machine learning code

A minimal implementation of Wasserstein GAN

Layers Outputs and Gradients in Keras. Made easy.

AoE (AI on Edge，终端智能，边缘计算) 是一个终端侧AI集成运行时环境 (IRE)，帮助开发者提升效率。

Extreme Learning Machine implemented in Pytorch

Label Embedding Network

Recurrent (conditional) generative adversarial networks for generating real-valued time series data.

Machine Learning Toolkit for Extreme Scale (MaTEx)

PyTorch implementation of NIPS 2017 paper Dynamic Routing Between Capsules

Deep Learning From Scratch

CapsNet (Capsules Net) in Geoffrey E Hinton paper "Dynamic Routing Between Capsules" - State Of the Art

Implement Decoupled Neural Interfaces using Synthetic Gradients in Pytorch

Experiments for understanding disentanglement in VAE latent representations

This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"

Collection of generative models in Tensorflow

PyTorch tutorials A to Z

Pytorch implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Networks (DCGAN) for MNIST and CelebA datasets

Get started with Machine Learning in TensorFlow with a selection of good reads and implemented examples!

Handwritten digits classification from MNIST with TensorFlow on Android; Featuring Tutorial!

TI-pooling: transformation-invariant pooling for feature learning in Convolutional Neural Networks

Six snippets of code that made deep learning what it is today.

The implementation of Relativistic average GAN with Keras

A look at some simple autoencoders for the Cifar10 dataset, including a denoising autoencoder. Python code included.

A project designed to explore CNN and the effectiveness of RCNN on classifying the EMNIST dataset.

Invert the color of MNIST images with PyTorch

Implementation of a neural network from scratch in python.

This repository provides a Colab Notebook that shows how to use Spatial Transformer Networks inside CNNs in Keras.

Pytorch、Scikit-learn实现多种分类方法，包括逻辑回归（Logistic Regression）、多层感知机（MLP）、支持向量机（SVM）、K近邻（KNN）、CNN、RNN，极简代码适合新手小白入门，附英文实验报告（ACM模板）

Simple Keras implementation of Triplet-Center Loss on the MNIST dataset

tensorflow implementation of Exploring Randomly Wired Neural Networks for Image Recognition

Using various CNN techniques on the MNIST dataset

Real-time Number Recognition using Apple's CoreML 2.0 and MNIST -

Implementation of ews weight constraint mentioned in recent Deep Mind paper: http://www.pnas.org/content/early/2017/03/13/1611835114.full.pdf

Tensorflow implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Adversarial Networks (cDCGAN) for MANIST dataset.

Generative Probabilistic Novelty Detection with Adversarial Autoencoders

Adventures using keras on Google's Cloud ML Engine

Theano implementation of XNOR-Net