Tech Xplore

New graph attention network models higher-order relationships in complex graph data

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
Investopedia

Bell Curve: Definition, How It Works, and Example

Andrew Bloomenthal has 20+ years of editorial experience as a financial journalist and as a financial services marketing writer. Samantha (Sam) Silberstein, CFP®, CSLP®, EA, is an experienced ...
IEEE

Multimodal Fault Diagnosis Method Based on Node-Level Adaptive Attention and Dynamic Graph Learning

Abstract: To address the challenges of acoustic and vibration signals being susceptible to noise interference, coarse modality fusion, and static graph structures in industrial fault diagnosis, we ...
IEEE

FedSGProx: Mitigating Data Heterogeneity and Isolated Nodes in Graph Federated Learning

Abstract: Graphs capture complex node interactions and are a fundamental tool for machine learning. Graph Federated Learning (GFL) is a method that allows multiple clients to collaboratively train a ...
GitHub

GRAPHINE: Enhancing Spatiotemporal Supply Chain Forecasting Using Virtual Node-Augmented Graph Diffusion for Improved Fuel Efficiency

Spatiotemporal forecasting in supply chain networks demands modeling complex spatial dependencies and nonlinear temporal dynamics. Traditional models often fail to capture the heterogeneity, ...