autoencoder-mnist
There are 77 repositories under autoencoder-mnist topic.
ReyhaneAskari/pytorch_experiments
Auto Encoders in PyTorch
abhisheksambyal/Autoencoders-using-Pytorch-Medical-Imaging
Medical Imaging, Denoising Autoencoder, Sparse Denoising Autoencoder (SDAE) End-to-end and Layer Wise Pretraining
nmeripo/Reducing-the-Dimensionality-of-Data-with-Neural-Networks
Implementation of G. E. Hinton and R. R. Salakhutdinov's Reducing the Dimensionality of Data with Neural Networks (Tensorflow)
eugenet12/pytorch-rbm-autoencoder
Pytorch implementation of an autoencoder built from pre-trained Restricted Boltzmann Machines (RBMs)
Mind-the-Pineapple/adversarial-autoencoder
Tensorflow 2.0 implementation of Adversarial Autoencoders
satolab12/anomaly-detection-using-autoencoder-PyTorch
encoder-decoder based anomaly detection method
fdavidcl/ae-review-resources
Additional resources for an overview on autoencoders
arunarn2/AutoEncoder
Stacked Denoising and Variational Autoencoder implementation for MNIST dataset
captain-pool/MNIST_AutoEncoder
AutoEncoder on MNIST Digit
codeperfectplus/autoEncoders
Deep convolutional autoencoder for image denoising
sarthak268/Deep_Neural_Networks
This repository contains Pytorch files that implement Basic Neural Networks for different datasets.
ariss95/image_reconstructon_examples
image reconstruction with pytorch
LorenzoValente3/Autoencoder-for-FPGA
Autoencoder model for FPGA implementation using hls4ml. Repository for Applied Electronics Project.
braininahat/CVIP-CSE573
UB Computer Vision
MatejBabis/TensorFlow2Autoencoder
Basic deep fully-connected autoencoder in TensorFlow 2
samridhishree/Deeplearning-Models
Deep learning models in Python
spyros-briakos/AutoEncoder-and-Classifier-of-MNIST-images
Implementation of an Auto-Encoder and Classifier so as to classify images from MNIST dataset.
A-Raafat/Classifiers-and-MNIST-Data
Extracting features using PCA, DCT, Centroid features and Auto encoder of 1 hidden-layer then classifying using K-means, GMM, SVM
Gauravshahare/ADVERSIAL_AUTOENCODER
Implementation of paper (https://arxiv.org/abs/1511.05644) for my own research
LorenzoValente3/Deep-Learning-Models
Keras implementation of Deep Learning Models applied to the MNIST and Polynomial datasets. Repository for the Software and Computing for Nuclear and Subnuclear Physics Project.
priyavrat-misra/image-compression-cae
Image compression using Convolutional Autoencoders.
saurabhkemekar/Denoising-Autoencoders
This project contains implementation of denoising autoencoder
07Agarg/Unsupervised-Learning
This repository contains Autoencoders, Variational Autoencoders and GANS-Unsupervised Models developed for MNIST Dataset in Tensorflow and PyTorch.
favalos/autoencoder-mxnet-scala
Simple implementation of Autoencoder with mxnet and scala.
martinetoering/Visual-Representation-Learning-Tutorials
Project materials for teaching bachelor students about fundamentals on Deep learning, PyTorch, ConvNets & Autoencoder (January, 2021).
Ninoko/Autoencoders
Different models of autoencoders: shallow, deep, convolutional, VAE, IWAE, DVAE, DIWAE
princeGedeon/Auto_encoder_with_tensorflow
Auto encoder pour la reduction de dimensionnalité d'un dataset en 2D ou en 3D pour mieux visionner et aussi pour la suppression de bruit sur des données images (Cas MNIST)
sayannath/Noise-Reduction-using-Auto-Encoders
Noise Reduction of Images using Auto Encoders.
shivchander/mnist-multilayer-feedforward
Multi Class Classification and Autoencoder for MNIST Dataset using Multi Layer Feed Forward Neural Net implemented from scratch
kamrul-brur/Auto-Encoder-Transformation-Model-From-Handwritten-to-Font-Digits
This project focuses on utilizing an autoencoder model to generate font digit images that correspond to handwritten digit images.
Raghul-G2002/DeepLearning_Sample_Notebooks
This repository consists of sample notebook which can take you through the basic deep learning excersises in Tensorflow and Pytorch
suryansh-sinha/AutoEncoders
PyTorch implementations of an Undercomplete Autoencoder and a Denoising Autoencoder that learns a lower dimensional latent space representation of images from the MNIST dataset.
zoli333/WinnerTakeAll
Pythorch implementation of Winner-Take-All Autoencoder