In this article, in order to better handle this problem, a novel generative model named the conditional variational autoencoder with an adversarial training process (CVA 2 E) is proposed for ...

Abstract: To deal with the typically insufficiently labeled samples involved in practical spectroscopy measurements, a conditional variational autoencoder (CVAE) is proposed to guide the spectral data ...

Variational Autoencoder in tensorflow and pytorch Reference implementation for a variational autoencoder in TensorFlow and PyTorch. I recommend the PyTorch version. It includes an example of a more ...

This paper is a valuable step in multi-subject behavioral modeling using an extension of the Variational Autoencoder (VAE) framework. Using a novel partition of the latent space and in tandem with a ...

Variational autoencoder for protein sequences - add metal binding sites and generate sequences for novel topologies - psipred/protein-vae ...

These variants are based on multiple code transformation approaches, such as changing data structures, wrapping or unwrapping code in functions, adjusting loop bounds, etc. The team proposes an ...