Variational Diagrammatic Monte-Carlo Built on Dynamical Mean-Field Theory

Joint variational Autoencoders for Multimodal Imputation and Embedding (JAMIE)

[Pytorch] Minimal implementation of a Variational Autoencoder (VAE) with Categorical Latent variables inspired from "Categorical Reparameterization with Gumbel-Softmax".

State arrays for single particle tracking

Discrete Variational Autoencoder in PyTorch

automatic/analytical differentiation benchmark

Disentangling the latent space of a VAE.

Disentangled Variational Auto-Encoder in TensorFlow / Keras (Beta-VAE)

Experiments on Disentangled Representation Learning using Variational autoencoding algorithms

Code for Adversarial Approximate Inference for Speech to Laryngograph Conversion

Denoising Variational Autoencoder

Python toolbox for solving imaging continuous optimization problems.

TensorFlow implementation of the method from Variational Dropout Sparsifies Deep Neural Networks, Molchanov et al. (2017)

Implementations of autoencoder, generative adversarial networks, variational autoencoder and adversarial variational autoencoder

A simple variational autoencoder to generate images from MNIST. Implemented in TensorFlow.