Gordon cnnA small convolution neural network deep learning framework implemented in c++.
Vae Cvae MnistVariational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch
Gan TutorialSimple Implementation of many GAN models with PyTorch.
Tf VqvaeTensorflow Implementation of the paper [Neural Discrete Representation Learning](https://arxiv.org/abs/1711.00937) (VQ-VAE).
Vq VaeMinimalist implementation of VQ-VAE in Pytorch
Cnn From ScratchA scratch implementation of Convolutional Neural Network in Python using only numpy and validated over CIFAR-10 & MNIST Dataset
Gan MnistGenerative Adversarial Network for MNIST with tensorflow
Tensorflow Mnist CnnMNIST classification using Convolutional NeuralNetwork. Various techniques such as data augmentation, dropout, batchnormalization, etc are implemented.
NnpulearningNon-negative Positive-Unlabeled (nnPU) and unbiased Positive-Unlabeled (uPU) learning reproductive code on MNIST and CIFAR10
Tensorflow Mnist Gan DcganTensorflow implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Netwokrs for MNIST dataset.
Mnist drawThis is a sample project demonstrating the use of Keras (Tensorflow) for the training of a MNIST model for handwriting recognition using CoreML on iOS 11 for inference.
Capsule NetworksA PyTorch implementation of the NIPS 2017 paper "Dynamic Routing Between Capsules".
Tensorflow Mnist Cgan CdcganTensorflow implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Adversarial Networks (cDCGAN) for MANIST dataset.
Ti PoolingTI-pooling: transformation-invariant pooling for feature learning in Convolutional Neural Networks
GpndGenerative Probabilistic Novelty Detection with Adversarial Autoencoders
Dni.pytorchImplement Decoupled Neural Interfaces using Synthetic Gradients in Pytorch
Tf Exercise GanTensorflow implementation of different GANs and their comparisions
Mnist ClassificationPytorch、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)
MatexMachine Learning Toolkit for Extreme Scale (MaTEx)
EmnistA project designed to explore CNN and the effectiveness of RCNN on classifying the EMNIST dataset.
Ml codeA repository for recording the machine learning code
Ios Coreml MnistReal-time Number Recognition using Apple's CoreML 2.0 and MNIST -
Tsne CudaGPU Accelerated t-SNE for CUDA with Python bindings
MultidigitmnistCombine multiple MNIST digits to create datasets with 100/1000 classes for few-shot learning/meta-learning
Ml In TfGet started with Machine Learning in TensorFlow with a selection of good reads and implemented examples!
Svhn CnnGoogle Street View House Number(SVHN) Dataset, and classifying them through CNN
Deep Generative ModelsDeep 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)
Randwire tensorflowtensorflow implementation of Exploring Randomly Wired Neural Networks for Image Recognition
KeractLayers Outputs and Gradients in Keras. Made easy.
Mnist EwcImplementation of ews weight constraint mentioned in recent Deep Mind paper: http://www.pnas.org/content/early/2017/03/13/1611835114.full.pdf
AoeAoE (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。
RganRecurrent (conditional) generative adversarial networks for generating real-valued time series data.
Capsnet PytorchPyTorch implementation of NIPS 2017 paper Dynamic Routing Between Capsules