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 ...
IEEE

ScaDyG: A New Paradigm for Large-Scale Dynamic Graph Learning

Abstract: Dynamic graphs (DGs), which capture time-evolving relationships between graph entities, have widespread real-world applications. To efficiently encode DGs for downstream tasks, most DG ...
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 ...
Frontiers

Multimodal graph neural networks in healthcare: a review of fusion strategies across biomedical domains

1 Department of Analytics, Harrisburg University of Science and Technology, Harrisburg, PA, United States 2 Department of Emergency Medicine, UMass Chan Medical School, Worcester, MA, United States ...
AlphaGalileo

A survey of dynamic graph neural networks

Dynamic Graph Neural Networks (Dynamic GNNs) have emerged as powerful tools for modeling real-world networks with evolving topologies and node attributes over time. A survey by Professors Zhewei Wei, ...