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 ...
IEEE

DTFL: A Digital Twin-Assisted Graph Neural Network Approach for Service Function Chains Failure Localization

Abstract: Cloud computing enables Network Function Virtualization to dynamically provide and deploy network functions (NFs) to meet business-specific requirements. This approach streamlines NFs’ ...
IEEE

Neural Acceleration of Graph Based Utility Functions for Sparse Matrices

Abstract: Many graph-based algorithms in high performance computing (HPC) use approximate solutions due to having algorithms that are computationally expensive or serial in nature. Neural acceleration ...
theregister

Neo4j plots Palantir alternative with GraphAware acquisition

"The no-kill-switch kind of thing? It's increasingly becoming a requirement," says Neo4j CEO Emil Eifrem. This is one of the reasons behind the company's decision to buy GraphAware, an intelligence ...