beta-vae

A Collection of Variational Autoencoders (VAE) in PyTorch.

Experiments for understanding disentanglement in VAE latent representations

Dataset to assess the disentanglement properties of unsupervised learning methods

Pytorch implementation of β-VAE

Replicating "Understanding disentangling in β-VAE"

Pytorch implementation of FactorVAE proposed in Disentangling by Factorising(http://arxiv.org/abs/1802.05983)

Easy generative modeling in PyTorch.

Repository for implementation of generative models with Tensorflow 1.x

🧶 Modular AE and VAE Disentanglement Framework built with PyTorch Lightning, including common datasets, metrics and visualisation. Optionally supporting easy configuration and running using Hydra Config with logging to W&B.

Predicting image frames using autoencoder and LSTM

Official PyTorch implementation on ID-GAN: High-Fidelity Synthesis with Disentangled Representation by Lee et al., 2020.

Anomaly detection on the UC Berkeley milling data set using a disentangled-variational-autoencoder (beta-VAE). Replication of results as described in article "Self-Supervised Learning for Tool Wear Monitoring with a Disentangled-Variational-Autoencoder"

An implementation of Denoising Variational AutoEncoder with Topological loss

Pytorch implementation of SCAN: Learning Hierarchical Compositional Visual Concepts, Higgins et al., ICLR 2018

generate arbitrary handwritten letter/digits based on the inputs

Using Beta VAE to test on faces of animal

Implementation of VAE in pytorch.

Pytorch implementation of a simple beta vae on dsprites data

Spatial Broadcast Decoder implementation in PyTorch on top of Docker.

A flexible framework of neural networks for deep learning

It's a repo for figuring out ways how to get automatic text summaries to Auto-ML models that perform regression (get compressed and factorized latent representation). Ideally it should be even able to answer questions on properties of that model.

Dataset to assess the disentanglement properties of unsupervised learning methods

the same as official VAE example, but using Trainer in this repo