GitHub

FedDGL: Federated Dynamic Graph Learning for Temporal Evolution and Data Heterogeneity

Federated graph learning advances the field of federated learning by enabling privacy-preserving collaborative training on distributed graph data. Conventional federated graph learning methods excel ...

ON Semiconductor: A Big Cyclical Recovery Is Around The Corner

ON Semiconductor Corporation sees AI growth, intelligent power tailwinds, a $6B buyback, and an emerging uptrend. Find out ...
GitHub

CGBridge: Bridging Code Graphs and Large Language Models for Better Structure-Aware Code Understanding

CGBridge is a novel framework designed to enhance the code understanding capabilities of Large Language Models (LLMs) by integrating rich structural information from code graphs. Our approach follows ...

OMRON Introduces DX100 Data Flow Edge Device for Fast, Secure Industrial Data Collection

Omron Automation has released the DX100 Data Flow Edge Device, an industrial edge solution designed to connect directly to ...
IEEE

Hypergraph Collaborative Filtering With Adaptive Augmentation of Graph Data for Recommendation

Abstract: Self-supervised tasks show significant advantages for node representation learning in recommender systems. This core idea of self-supervised task-based recommender systems depends on data ...
IEEE

STMGCN: A Spatiotemporal Multi-Graph Convolutional Networks for Real-Time Intelligent Transportation Traffic Flow Prediction

Abstract: The Internet of Things (IoT) and artificial intelligence (AI) are essential for intelligent transportation systems (ITS) because they allow for real-time decision-making, predictive ...