Abstract: Dimensionality reduction using Variational Autoencoder (VAE) is widely employed in learning diverse state representations, such as in autonomous driving tasks. Conventional VAE-based ...

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 ...

Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems, School of Engineering, Huzhou University, Huzhou 313000, PR China Zhejiang Key Laboratory of Industrial Solid ...

VANCOUVER, British Columbia--(BUSINESS WIRE)--Variational AI, the company behind Enki™, an advanced foundation model for small molecule drug discovery, today ...

Abstract: Variational Autoencoder(VAE) combines the ideas of autoencoders and variational inference, introducing the concept of latent space and variational inference to endow autoencoders to generate ...

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 ...

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 ...

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