GitHub - Sission/Coupled-VAE-Improved-Robustness-and-Accuracy-of-a-Variational-Autoencoder: We present a coupled Variational Auto-Encoder (VAE) method that improves the accuracy and robustness of the ...

Article citations More>> Jin, W., Barzilay, R. and Jaakkola, T. (2018) Junction Tree Variational Autoencoder for Molecular Graph Generation. International Conference on Machine Learning, Stockholm, 10 ...

In this article, a conditional variational autoencoder based method is proposed for the probabilistic wind power curve modeling task. To advance the modeling performance, the latent random variable is ...

Variational Autoencoder with Arbitrary Conditioning (VAEAC) is a neural probabilistic model based on variational autoencoder that can be conditioned on an arbitrary subset of observed features and ...

A variational autoencoder (VAE) is a deep neural system that can be used to generate synthetic data. VAEs share some architectural similarities with regular neural autoencoders (AEs) but an AE is not ...

There are research efforts to complement an autoencoder with an advanced type of autoencoder called a variational autoencoder (VAE). VAEs tend to underfit so the idea is to combine a basic autoencoder ...