GitHub

STM-Graph: A Python Framework for Spatio-Temporal Mapping and Graph Neural Network Predictions

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...
Redding Record Searchlight

Shasta County sues social media companies, claiming apps are addictive, harm teens

Shasta County officials filed a lawsuit claiming online social media and internet search engine companies have been luring youth into using networking platforms that are harmful at their age. The ...
Frontiers

Graph neural networks with configuration cross-attention for tensor compilers

With the recent popularity of neural networks comes the need for efficient serving of inference workloads. A neural network inference workload can be represented as a computational graph with nodes as ...
C&EN

Multilevel Fusion Graph Neural Network for Molecule Property Prediction

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.5c01525. Efficiency analysis of different normalization strategies ...
IEEE

CSCL-GNN: Cross-View Semantic Contrastive Learning and Graph Neural Networks for Event Recommendation in Event-Based Social Networks

Abstract: Event-based social networks (EBSNs) connect users through shared interests in real-world events. These platforms allow users to discover, join, and interact around events, but their complex ...
Scientific Research Publishing

Li, W., Ma, W., Yang, M. and Tang, X. (2024) Drug Repurposing Based on the DTD-GNN Graph Neural Network: Revealing the Relationships among Drugs, Targets and Diseases. BMC ...

ABSTRACT: Drug repositioning aims to identify new therapeutic applications for existing drugs offering a faster and more cost-effective alternative to traditional drug discovery. Since approved drugs ...
Semiconductor Engineering

GNN-Based Framework for Hardware Trojan Detection, Including RISC-V Cores

A new technical paper titled “TROJAN-GUARD: Hardware Trojans Detection Using GNN in RTL Designs” was published by researchers at University of Connecticut and University of Minnesota. “hip ...
Scientific Research Publishing

Gordon, D., Petousis, P., Zheng, H., Zamanzadeh, D. and Bui, A.A.T. (2021) TSI-GNN: Extending Graph Neural Networks to Handle Missing Data in Temporal Settings. Frontiers in ...

ABSTRACT: Missing data remains a persistent and pervasive challenge across a wide range of domains, significantly impacting data analysis pipelines, predictive modeling outcomes, and the reliability ...