autoencoders
There are 476 repositories under autoencoders topic.
serengil/tensorflow-101
TensorFlow 101: Introduction to Deep Learning
curiousily/Deep-Learning-For-Hackers
Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)
aapatel09/handson-unsupervised-learning
Code for Hands-on Unsupervised Learning Using Python (O'Reilly Media)
curiousily/Credit-Card-Fraud-Detection-using-Autoencoders-in-Keras
iPython notebook and pre-trained model that shows how to build deep Autoencoder in Keras for Anomaly Detection in credit card transactions data
khanhnamle1994/MetaRec
PyTorch Implementations For A Series Of Deep Learning-Based Recommendation Models
aqibsaeed/Place-Recognition-using-Autoencoders-and-NN
Place recognition with WiFi fingerprints using Autoencoders and Neural Networks
vuptran/graph-representation-learning
Autoencoders for Link Prediction and Semi-Supervised Node Classification (DSAA 2018)
nathanhubens/Autoencoders
Implementation of simple autoencoders networks with Keras
CompVis/net2net
Network-to-Network Translation with Conditional Invertible Neural Networks
harveyslash/Deep-Steganography
Hiding Images within other images using Deep Learning
pcko1/Deep-Drug-Coder
A tensorflow.keras generative neural network for de novo drug design, first-authored in Nature Machine Intelligence while working at AstraZeneca.
milaan9/Deep_Learning_Algorithms_from_Scratch
This repository explores the variety of techniques and algorithms commonly used in deep learning and the implementation in MATLAB and PYTHON
alexandru-dinu/cae
Compressive Autoencoder.
numaproj/numalogic
Collection of operational time series ML models and tools
cwkx/GON
Gradient Origin Networks - a new type of generative model that is able to quickly learn a latent representation without an encoder
rezacsedu/Deep-Learning-for-Clustering-in-Bioinformatics
Deep Learning-based Clustering Approaches for Bioinformatics
nmichlo/disent
🧶 Modular VAE disentanglement framework for python built with PyTorch Lightning ▸ Including metrics and datasets ▸ With strongly supervised, weakly supervised and unsupervised methods ▸ Easily configured and run with Hydra config ▸ Inspired by disentanglement_lib
dr-costas/mad-twinnet
The code for the MaD TwinNet. Demo page:
FutureXiang/ddae
[ICCV 2023 Oral] Official Implementation of "Denoising Diffusion Autoencoders are Unified Self-supervised Learners"
lhao499/language-quantized-autoencoders
Language Quantized AutoEncoders
skolouri/swae
Implementation of the Sliced Wasserstein Autoencoders
timothyyu/wsae-lstm
implementation of WSAE-LSTM model as defined by Bao, Yue, Rao (2017)
hamaadshah/autoencoders_tensorflow
Automatic feature engineering using deep learning and Bayesian inference using TensorFlow.
jbramburger/DataDrivenDynSyst
Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems
greenelab/adage
Data and code related to the paper "ADAGE-Based Integration of Publicly Available Pseudomonas aeruginosa..." Jie Tan, et al · mSystems · 2016
ReyhaneAskari/pytorch_experiments
Auto Encoders in PyTorch
nikhil-dce/Transforming-Autoencoder-TF
Tensorflow implementation of "Transforming Autoencoders" (Proposed by G.E.Hinton, et al.)
FutureXiang/soda
Unofficial implementation of "SODA: Bottleneck Diffusion Models for Representation Learning"
wanglouis49/pytorch-autoencoders
Implementation of autoencoders in PyTorch
avijit9/Contractive_Autoencoder_in_Pytorch
Pytorch implementation of contractive autoencoder on MNIST dataset
mpatacchiola/Y-AE
Official Tensorflow implementation of the paper "Y-Autoencoders: disentangling latent representations via sequential-encoding", Pattern Recognition Letters (2020)
ImKeTT/CTG-latentAEs
[Paperlist] Awesome paper list of controllable text generation via latent auto-encoders. Contributions of any kind are welcome.
xavierfav/coala
COALA: Co-Aligned Autoencoders for Learning Semantically Enriched Audio Representations
haimengzhao/CAE-ADMM
CAE-ADMM: Implicit Bitrate Optimization via ADMM-Based Pruning in Compressive Autoencoders
EthanJamesLew/AutoKoopman
AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.
abhisheksambyal/Autoencoders-using-Pytorch-Medical-Imaging
Medical Imaging, Denoising Autoencoder, Sparse Denoising Autoencoder (SDAE) End-to-end and Layer Wise Pretraining