Abstract: Metamaterials have experienced rapid development in recent years. Absorbers made of metamaterials play a crucial role in electromagnetic applications and other fields. The design of ...

scVAG is an innovative framework that integrates Variational Autoencoder (VAE) and Graph Attention Autoencoder (GATE) models for enhanced analysis of single-cell gene expression data. Built upon the ...

Generating the periodic structure of stable materials is a long-standing challenge for the material design community. This task is difficult because stable materials only exist in a low-dimensional ...

ABSTRACT: Predicting molecular properties is essential for advancing for advancing drug discovery and design. Recently, Graph Neural Networks (GNNs) have gained prominence due to their ability to ...

This project provides a comprehensive analysis of Variational Autoencoders (VAE) and traditional Autoencoders (AE) for image compression tasks. The analysis focuses on the impact of various model ...

1 College of Computer and Control Engineering, Qiqihar University, Qiqihar, China 2 Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis, Qiqihar University, Qiqihar, China ...

Abstract: The research provides a comprehensive review of generative architectures built upon the Variational Autoencoder (VAE) paradigm, emphasizing their capacity to delineate latent structures ...

Department of Biochemistry, University of Washington, Seattle, Washington 98195, United States Institute for Protein Design, University of Washington, Seattle, Washington 98195, United States ...