Frontiers

Multimodal graph neural networks in healthcare: a review of fusion strategies across biomedical domains

1 Department of Analytics, Harrisburg University of Science and Technology, Harrisburg, PA, United States 2 Department of Emergency Medicine, UMass Chan Medical School, Worcester, MA, United States ...
IEEE

Modeling Relational Logic Circuits for And-Inverter Graph Convolutional Network

Abstract: The automation of logic circuit design enhances chip performance, energy efficiency, and reliability, and is widely applied in the field of Electronic Design Automation (EDA). And-Inverter ...
IEEE

RGCNs: Relational Graph Convolutional Networks for Trust-based Fraud Identification in SIoT

Abstract: Observing growing use of smart and Social Internet of Things (SIoT) devices, trust and security have become major concerns. As more users connect and interact, fraudsters take advantage of ...
pv magazine International

PV module fault diagnosis uses convolutional neural network

Researchers in China have created a dataset of various PV faults and normalized it to accommodate different array sizes and typologies. After testing the new approach in combination with the 1D-CNN ...
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 ...
EurekAlert!

Real-time, large-scale graph neural network inference through BingoCGN

BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...