In this study, we proposed HDVAE (Hierarchical Decoupled Variational Autoencoder) which significantly improved the identification ability of the spatial domain in ST data through multi-hop graph ...

To solve the mentioned challenges, we propose a combined architecture comprising a Conditional Variational AutoEncoder (CVAE) and a Random Forest (RF) classifier to automatically learn similarity ...

Designing bioactive molecules with desired properties for specific targets is a longstanding challenge in drug design. We introduce a model called BiAtt-GVAE, which incorporates a conditional to more ...

The variational autoencoder (VAE) was employed to reduce feature redundancy and to accomplish noise reduction. Some studies have been conducted using autoencoders (e.g., sparse autoencoder) to process ...