President Trump disregards them, technology is remaking them — in an age of upheaval, our maps are in flux too ...

Abstract: The nature of heterophilous graphs is significantly different from that of homophilous graphs, which causes difficulties in early graph neural network (GNN) models and suggests aggregations ...

Abstract: Graph matching aims to establish node correspondences between graphs, which is a classic combinatorial optimization problem. In recent years, (deep) learning-based methods have emerged as a ...

This repository contains code for Talk like a Graph: Encoding Graphs for Large Language Models and Let Your Graph Do the Talking: Encoding Structured Data for LLMs. @inproceedigs{fatemi2024talk, ...

GraphStorm is an enterprise-grade graph machine learning (GML) framework designed for scalability and ease of use. It simplifies the development and deployment of GML models on industry-scale graphs ...

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