132 Open source projects that are alternatives of or similar to Unsupervised_Deep_Learning

Convolutional Autoencoder for Loop Closure

Handle class imbalance intelligently by using variational auto-encoders to generate synthetic observations of your minority class.

A sparsity aware implementation of "Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection" (CIKM 2018).

Training and evaluating a variational autoencoder for pan-cancer gene expression data

PyTorch Blog Post On Image Similarity Search

텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다

Autoencoders in Keras

🌐 Deep Embedded Self-Organizing Map: Joint Representation Learning and Self-Organization

This repo includes the source code of the fully convolutional depth denoising model presented in https://arxiv.org/pdf/1909.01193.pdf (ICCV19)

Generative Adversarial Networks and Autoencoders for 3D Shapes

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Variational Recurrent Autoencoder for timeseries clustering in pytorch

Deep learning meets molecular dynamics.

Integrated Cell project implemented in pytorch

Deep Learning sample programs using PyTorch in C++

Image reconstruction done with untrained neural networks.

R, Python and Mathematica Codes in Machine Learning, Deep Learning, Artificial Intelligence, NLP and Geolocation

This is the official implementation for the paper 'AutoEncoder by Forest'

Using Deep Autoencoders for predictions of movie ratings.

Visualization techniques for the latent space of a convolutional autoencoder in Keras

[unmaintained] An open-source convolutional neural networks platform for research in medical image analysis and image-guided therapy

Representation learning for link prediction within social networks

PyTorch implementation of SDAE (Stacked Denoising AutoEncoder)

A simple Tensorflow based library for deep and/or denoising AutoEncoder.

Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction. In CVPR, 2017.

Python codes in Machine Learning, NLP, Deep Learning and Reinforcement Learning with Keras and Theano

Learning deep representations by mutual information estimation and maximization

PyTorch implementation of DEC (Deep Embedding Clustering)

Theano implementation of Sequence-to-Sequence Autoencoder

State Representation Learning (SRL) zoo with PyTorch - Part of S-RL Toolbox

Reference code for the paper: Deep White-Balance Editing, CVPR 2020 (Oral). Our method is a deep learning multi-task framework for white-balance editing.

rectorch is a pytorch-based framework for state-of-the-art top-N recommendation

Tensorflow implementation of adversarial auto-encoder for MNIST

Anomaly detection for streaming data using autoencoders

中文的 tensorflow tutorial with jupyter notebooks

Generative Probabilistic Novelty Detection with Adversarial Autoencoders

Using Autoencoders for classification as unsupervised machine learning algorithms with Deep Learning.

Detection of Accounting Anomalies using Deep Autoencoder Neural Networks - A lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.

Library of autoencoders for sequential data

Structural Deep Clustering Network

Hands-on in-person workshop for Deep Learning with TensorFlow

Tensorflow implementation : U-net and FCN with global convolution

MotionSense Dataset for Human Activity and Attribute Recognition ( time-series data generated by smartphone's sensors: accelerometer and gyroscope)

A Pytorch implementation for the ZeroSpeech 2019 challenge.

A curated list of dedicated resources and applications

PyTorch implementation of Soft Actor-Critic + Autoencoder(SAC+AE)

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

Keras implementation of Structural Deep Network Embedding, KDD 2016

Easy Reduced Basis method

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Implementation of the stacked denoising autoencoder in Tensorflow

Molecular AutoEncoder in PyTorch

A Variational Autoencoder (VAE) implemented in PyTorch

Focal Frequency Loss for Generative Models

Real time face landmarking using decision trees and NN autoencoders

Image retrieval program made in Tensorflow supporting VGG16, VGG19, InceptionV3 and InceptionV4 pretrained networks and own trained Convolutional autoencoder.

Tensorflow 2.0 implementation of Adversarial Autoencoders

Tensorflow implementation of Adversarial Autoencoders

Tensorflow implementation of conditional variational auto-encoder for MNIST