autoencoders
There are 554 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)
AutoViML/featurewiz
Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshadri. Collaborators welcome.
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
[DSAA 2018] Autoencoders for Link Prediction and Semi-Supervised Node Classification
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.
FutureXiang/ddae
[ICCV 2023 Oral] Official Implementation of "Denoising Diffusion Autoencoders are Unified Self-supervised Learners"
alexandru-dinu/cae
Compressive AutoEncoder.
numaproj/numalogic
Collection of operational time series ML models and tools
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
cwkx/GON
Gradient Origin Networks - a new type of generative model that is able to quickly learn a latent representation without an encoder
yinboc/dito
Official PyTorch Implementation of "Diffusion Autoencoders are Scalable Image Tokenizers"
jbramburger/DataDrivenDynSyst
Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems
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
vmicheli/delta-iris
Efficient World Models with Context-Aware Tokenization. ICML 2024
dr-costas/mad-twinnet
The code for the MaD TwinNet. Demo page:
haoliuhl/language-quantized-autoencoders
Language Quantized AutoEncoders
FutureXiang/soda
Unofficial implementation of "SODA: Bottleneck Diffusion Models for Representation Learning"
skolouri/swae
Implementation of the Sliced Wasserstein Autoencoders
BenChaliah/Superposition-Transformer
a novel architecture that leverages Autoencoders to superimpose the hidden representations of a base model and a fine-tuned model within a shared parameter space. Using B-spline-based blending coefficients and autoencoders that adaptively reconstruct the original hidden states based on the input data distribution.
xianglin226/Benchmarking-Single-Cell-Perturbation
Single-Cell (Perturbation) Model Library
EthanJamesLew/AutoKoopman
AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.
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.
AlexPasqua/Autoencoders
Pytorch implementation of various autoencoders (contractive, denoising, convolutional, randomized)
paucablop/chemotools
Integrate your chemometric tools with the scikit-learn API 🧪 🤖
ReyhaneAskari/pytorch_experiments
Auto Encoders in PyTorch
HROlive/Applications-of-AI-for-Anomaly-Detection
Nvidia DLI workshop on AI-based anomaly detection techniques using GPU-accelerated XGBoost, deep learning-based autoencoders, and generative adversarial networks (GANs) and then implement and compare supervised and unsupervised learning techniques.
nikhil-dce/Transforming-Autoencoder-TF
Tensorflow implementation of "Transforming Autoencoders" (Proposed by G.E.Hinton, et al.)