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 ...
GitHub

UrbanGraph: Physics-Informed Spatio-Temporal Dynamic Heterogeneous Graphs for Urban Microclimate Prediction

This repository contains the official PyTorch implementation and the UMC4/12 Dataset for the paper: [UrbanGraph: Physics-Informed Spatio-Temporal Dynamic Heterogeneous Graphs for Urban Microclimate ...
Scientific Research Publishing

Knowledge Graph Application in KM for Accounting and Supply Chain in SMEs ()

Knowledge Graph, Large Language Model, BERT, Knowledge Management, Small and Medium-Sized Enterprises, Accounting, Supply Chain Management Zheng, Y. (2026) Knowledge Graph Application in KM for ...
IEEE

Dynamic Graph Variational Sparse Coding for Power Distribution Network Fault Location and Classification

Abstract: Fault location and classification are crucial to the reliable and resilient operation of power distribution networks (PDNs). Current machine learning works cannot provide accurate and ...
GitHub

City2Graph: GeoAI with Graph Neural Networks (GNNs) and Spatial Network Analysis

This installs the core functionality without PyTorch and PyTorch Geometric. To use PyTorch and PyTorch Geometric with City2Graph installed from conda-forge, you need to manually add these libraries to ...
IEEE

CamFD: Semi-Supervised Camouflage-Aware Fraud Detection Based on Dynamic Graphs

Abstract: Fraud detection on dynamic graph (FDDG) is in high demand across many real-world applications, such as financial transaction networks and social networks. A graph neural network (GNN) is an ...