Variational Autoencoder Python Packages

scvi-tools

Deep probabilistic analysis of single-cell and spatial omics data

avitai-artifex

Generative modeling for JAX/Flax NNX: VAEs, GANs, DDPM/DDIM/score/DiT/latent diffusion, normalizing flows, energy-based, autoregressive and geometric (SE(3), protein, point cloud, mesh) models; image, text, audio, molecular, protein, tabular and time-series modalities; a shared Trainer with callbacks and extensions; evaluation through calibrax.

normflows

PyTorch implementation of normalizing flow models

focal-frequency-loss

[ICCV 2021] Focal Frequency Loss for Image Reconstruction and Synthesis

numalogic

Collection of operational time series ML models and tools

scvi

Deep probabilistic analysis of single-cell and spatial omics data

pythae

Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)

distvae-tabular

Official implementation of 'Distributional Learning of Variational AutoEncoder: Application to Synthetic Data Generation' (DistVAE) with pytorch (NeurIPS 2023 accepted paper).

nichecompass

End-to-end analysis of spatial multi-omics data

nhssynth

Package to accompany P41

move-dl

MOVE (Multi-Omics Variational autoEncoder) for integrating multi-omics data and identifying cross modal associations

pi-vae-pytorch

Implementation of Poisson Identifiable VAE (pi-VAE) in Pytorch

pyroved

Invariant representation learning from imaging and spectral data

ponyo

Software to simulate compendium-wide gene expression data using a VAE.

snpmanifold

Manifold learning for single-cell single-nucleotide genetic variations

deepgen

Collection of modern Deep Generative Models

claritycore

Next-generation Open Source toolkit for low-level vision. Engineered for state-of-the-art performance in image and video pixel2pixel tasks, including Super-Resolution, Denoising, Deblurring, and more.

pyraug

Data Augmentation with Variational Autoencoders (TPAMI)

rectorch

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

rapidae

Explore, compare and develop autoencoder models with a back-end agnostic framework

odin-ai

Orgainzed Digital Intelligent Network (O.D.I.N)

tfae

TensorFlow extension for building and training different types of autoencoders

antipode

Variational Inference for Cell Type Evolution

sisua

SemI-SUpervised generative Autoencoder models for single cell data