Variational Autoencoder (VAE) and Variational Bayesian methods Going through the code is almost the best way to explain the Variational Autoencoder. However, to fully understand Variational Bayesian ...

Combining the mean and log-variance in this way is called the reparameterization trick. The discovery of this idea in the original 2013 research paper ("Auto-Encoding Variational Bayes" by D.P. Kingma ...

The variational autoencoder (VAE) has been used in a myriad of applications, e.g., dimensionality reduction and generative modeling. VAE uses a specific model for stochastic sampling in latent space.

An implicit-derivative-based reparameterization trick enables the use of a gamma distribution in a variational autoencoder. The latent variables in the generative model are inferred using the ...

Variational Autoencoder When we regularize an autoencoder so that its latent representation is not overfitted to a single data point but the entire data distribution, we can perform random sampling ...