A Collection of Variational Autoencoders (VAE) in PyTorch.

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

There are C language computer programs about the simulator, transformation, and test statistic of continuous Bernoulli distribution. More than that, the book contains continuous Binomial distribution and continuous Trinomial distribution.

Implementation of a Hybrid Variational Autoencoder (VAE) for label information-guided dimensionality reduction.

Tensorflow 2.x implementation of the beta-TCVAE (arXiv:1802.04942).

Pytorch implementation of Gaussian Mixture Variational Autoencoder GMVAE

An official repository for a VAE tutorial of Probabilistic Modelling and Reasoning (2023/2024) - a University of Edinburgh master's course.

Python implementation of N-gram Models, Log linear and Neural Linear Models, Back-propagation and Self-Attention, HMM, PCFG, CRF, EM, VAE

Variational Auto Encoders (VAEs), Generative Adversarial Networks (GANs) and Generative Normalizing Flows (NFs) and are the most famous and powerful deep generative models.

Implementation of the variational autoencoder with PyTorch and Fastai

Implementation of CVAE. Trained CVAE on faces from UTKFace Dataset to produce synthetic faces with a given degree of happiness/smileyness.

A re-implementation of the Sentence VAE paper, Generating Sentences from a Continuous Space

Towards Generative Modeling from (variational) Autoencoder to DCGAN

Pytorch版本实现的VAE和公式推导

Autoencoders (Standard, Convolutional, Variational), implemented in tensorflow

VAE and CVAE pytorch implement based on MNIST

Testing the Reproducibility of the paper: MixSeq. Under the assumption that macroscopic time series follow a mixture distribution, they hypothesise that lower variance of constituting latent mixture components could improve the estimation of macroscopic time series.

Built a model to create highlights/summary of given video. The results of this study shows that, with a remarkable similarity index(SSIM) of 98%, the recommended technique is quite successful in choosing keyframes that are both educational and distinctive from the original movie

Running VAEs on mobile and IOT devices using TFLite.