Abstract: Recommendation systems play a crucial role in uncovering concealed interactions among users and items within online social networks. Recently, Graph Neural Network (GNN)-based recommendation ...
Dual Graph Convolutional Network for Hyperspectral Images With Spatial Graph and Spectral Multigraph
Abstract: To accurately represent the graph structure of the pixel nodes in the hyperspectral remote sensing image classification based on graph convolutional networks (GCNs), a spectral multigraph ...
Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?
CSA's AICM v1.1 expands the AI security framework into a bundled control, assessment, audit and standards-mapping package.
Heterogeneous Graph Transformer is a graph neural network architecture that can deal with large-scale heterogeneous and dynamic graphs. You can see our WWW 2020 paper “Heterogeneous Graph Transformer” ...
This repository contains the code and data for the experiments in the paper "Discovering network dynamics with neural symbolic regression", published in Nature Computational Science (2025). Abstract: ...
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