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

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

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

Denoising Variational Autoencoder

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

Deep Probabilistic Programming Examples in Pytorch using pyro

Joint variational Autoencoders for Multimodal Imputation and Embedding (JAMIE)

probabilistic graphical model collections

State arrays for single particle tracking

Disentangling the latent space of a VAE.

Some basic implementations of Variational Autoencoders in pytorch

Code for Adversarial Approximate Inference for Speech to Laryngograph Conversion

Efficient C implementation of Quantum Analytic Descent

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

automatic/analytical differentiation benchmark

Anomaly detection in time series

Discrete Variational Autoencoder in PyTorch

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