This repository presents an implementation of a Variational Autoencoder (VAE) tailored for the generation ... Advanced VAE architecture optimized for high-dimensional protein structure data. Seamless ...

Currently two models are supported, a simple Variational Autoencoder and a Disentangled version (beta-VAE). The model implementations can be found in the src/models directory. These models were ...

Molecular dynamics (MD) simulations have been actively used in the study of protein structure and function. However, extensive sampling in the protein conformational space requires large computational ...

To resolve this problem, we first propose a neighborhood geometric structure-preserving variational autoencoder (SP-VAE), which not only maximizes the evidence lower bound but also encourages latent ...

Generating the periodic structure of stable materials is a long-standing ... We propose a Crystal Diffusion Variational Autoencoder (CDVAE) that captures the physical inductive bias of material ...

Learning Community Structure with Variational Autoencoder Abstract: Discovering community structure in networks remains a fundamentally challenging task. From scientific domains such as biology, ...

2 Loop closure detection system architecture based on variational autoencoder Figure 1 shows the structure of the proposed loop closure detection system based on a variational autoencoder. Dividing ...