autoencoder

There are 1960 repositories under autoencoder topic.

  • handson-ml

    도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.

    Language:Jupyter Notebook290

  • SDCN

    Structural Deep Clustering Network

    Language:Python284

  • awesome-tensorlayer

    A curated list of dedicated resources and applications

    270

  • image_similarity

    PyTorch Blog Post On Image Similarity Search

    Language:Python257

  • pytorch_cpp

    Deep Learning sample programs using PyTorch in C++

    Language:C++254

  • pytorch_sac_ae

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

    Language:Python251

  • adversarial-autoencoders

    Tensorflow implementation of Adversarial Autoencoders

    Language:Python247

  • KitNET-py

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

    Language:Python244

  • deep_image_prior

    Image reconstruction done with untrained neural networks.

    Language:Python221

  • CodeSLAM

    Implementation of CodeSLAM — Learning a Compact, Optimisable Representation for Dense Visual SLAM paper (https://arxiv.org/pdf/1804.00874.pdf)

    Language:Python207

  • deepAI

    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.

    Language:Jupyter Notebook207
  • DANMF

    DANMF

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

    Language:Python206

  • tensorflow_stacked_denoising_autoencoder

    Implementation of the stacked denoising autoencoder in Tensorflow

    Language:Python205

  • calc

    Convolutional Autoencoder for Loop Closure

    Language:Python201

  • LSTM-Autoencoders

    Anomaly detection for streaming data using autoencoders

    Language:Python201

  • Noise2Noise-audio_denoising_without_clean_training_data

    Source code for the paper titled "Speech Denoising without Clean Training Data: a Noise2Noise Approach". Paper accepted at the INTERSPEECH 2021 conference. This paper tackles the problem of the heavy dependence of clean speech data required by deep learning based audio denoising methods by showing that it is possible to train deep speech denoising networks using only noisy speech samples.

    Language:Jupyter Notebook198

  • LatentSpaceVisualization

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

    Language:Python196

  • Tensorflow-101

    中文的 tensorflow tutorial with jupyter notebooks

    Language:Jupyter Notebook188

  • Unsupervised_Anomaly_Detection_Brain_MRI

    Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study

    Language:Python186

  • deeptime

    Deep learning meets molecular dynamics.

    Language:Jupyter Notebook185

  • tybalt

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

    Language:HTML172

  • srl-zoo

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

    Language:Python163

  • tmu

    Implements the Tsetlin Machine, Coalesced Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, and Weighted Tsetlin Machine, with support for continuous features, drop clause, Type III Feedback, focused negative sampling, multi-task classifier, autoencoder, literal budget, and one-vs-one multi-class classifier. TMU is written in Python with wrappers for C and CUDA-based clause evaluation and updating.

    Language:Python155

  • eqvae

    [ICML'25] EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling.

    Language:Python153
  • rectorch

    rectorch

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

    Language:Python151

  • topological-autoencoders

    Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.

    Language:Python150

  • tensorflow-mnist-CVAE

    Tensorflow implementation of conditional variational auto-encoder for MNIST

    Language:Python150

  • libsdae-autoencoder-tensorflow

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

    Language:Python149

  • KATE

    Code & data accompanying the KDD 2017 paper "KATE: K-Competitive Autoencoder for Text"

    Language:Python146

  • Network-Intrusion-Detection-Using-Machine-Learning

    A Novel Statistical Analysis and Autoencoder Driven Intelligent Intrusion Detection Approach

    Language:Jupyter Notebook141

  • CADE

    Code for our USENIX Security 2021 paper -- CADE: Detecting and Explaining Concept Drift Samples for Security Applications

    Language:Python141

  • splitbrainauto

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

    Language:Shell141

  • DataDrivenDynSyst

    Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems

    Language:Jupyter Notebook140

  • MLwithTensorFlow2ed

    Code for Machine Learning with TensorFlow: 2nd Edition Published by Manning Publications

    Language:Jupyter Notebook140

  • fault-detection-for-predictive-maintenance-in-industry-4.0

    This research project will illustrate the use of machine learning and deep learning for predictive analysis in industry 4.0.

    Language:Jupyter Notebook138
  • AutoEncoder-Based-Communication-System

    AutoEncoder-Based-Communication-System

    Tensorflow Implementation and result of Auto-encoder Based Communication System From Research Paper : "An Introduction to Deep Learning for the Physical Layer" http://ieeexplore.ieee.org/document/8054694/

    Language:Jupyter Notebook135