Scientific Research Publishing

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ()

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ...
C&EN

Enhanced Prediction of Absorption and Emission Wavelengths of Organic Compounds through Hybrid Graph Neural Network Architectures

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Despite these advancements, predicting absorption and emission ...
The New York Times

Supreme Court Allows Mississippi Law on Children’s Use of Social Media, for Now

A trade group representing sites like Facebook and X said the law ran afoul of the First Amendment. By Adam Liptak and Zach Montague Reporting from Washington The Supreme Court on Thursday refused to ...
C&EN

GGCRB: A Graph Neural Network Approach for Predicting CircRNA–RBP Interactions Using Structural and Sequence Features

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The interaction between circular RNAs (circRNAs) and RNA-binding proteins (RBPs) plays ...
IEEE

Cross-Domain Explainable Recommendation Using Graph Convolutional Networks and a Topic Model

Abstract: Graph Convolutional Network (GCN)-based recommendation systems (RSs) have recently gained popularity for their ability to improve recommendation accuracy by utilizing neighborhood ...
Frontiers

A multi-graph convolutional network method for Alzheimer’s disease diagnosis based on multi-frequency EEG data with dual-mode connectivity

Objective: Alzheimer’s disease (AD) is mainly identified by cognitive function deterioration. Diagnosing AD at early stages poses significant challenges for both researchers and healthcare ...
IEEE

HS-GCN: A High-Performance, Sustainable, and Scalable Chiplet-Based Accelerator for Graph Convolutional Network Inference

Abstract: Graph Convolutional Networks (GCNs) have been proposed to extend machine learning techniques for graph-related applications. A typical GCN model consists of multiple layers, each including ...
Frontiers

Dual graph-embedded fusion network for predicting potential microbe-disease associations with sequence learning

Recent studies indicate that microorganisms are crucial for maintaining human health. Dysbiosis, or an imbalance in these microbial communities, is strongly linked to a variety of human diseases.