Autoencoders Python Packages

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.

augmented-pca

Repository for the AugmentedPCA Python package.

numalogic

Collection of operational time series ML models and tools

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

chuchichaestli

Where you find all the state-of-the-art cooking utensils (salt, pepper, gradient descent... the usual).

fraud-detection-autoencoders

Use autoencoders to detect fraud samples.

segmentae

SegmentAE: A Python Library for Anomaly Detection Optimization

autokoopman

AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.

biopy

Multi-omics translations through the usage of multiple uncoupled autoencoders sharing a common latent space

pressio4py

pressio4py: projection-based model reduction for Python

mmae

Package for multimodal autoencoders with Bregman divergences.

gimmick

Libraray contains algo to generate images by learning representation from data

dimae

Dimensionality Reduction Autoencoder built in TF Keras

easyae-samuel-revolinski

This repository if for creating auto-encoders easily. The main focus of the auto-encoders on this page is for genetic and spectral data analysis but likely could be used for any high dimensional data

easyae

This repository if for creating auto-encoders easily. The main focus of the auto-encoders on this page is for genetic and spectral data analysis but likely could be used for any high dimensional data

lscae

Deep unsupervised feature selection by discarding nuisance and correlated features