Graph Neural Networks (GNNs) are widely used across fields, with inductive learning replacing transductive learning as the mainstream training paradigm due to its superior memory efficiency, ...

In this paper, we propose ST-LLM+, the graph enhanced spatio-temporal large language models for traffic prediction. Through incorporating a proximity-based adjacency matrix derived from the traffic ...

This repository maintains 31 benchmark graph datasets, which are widely used for graph classification. The graph datasets consist of: chemical compounds citation networks social networks brain ...

Nature PortfolioOn this page Plagiarism and fabrication Due credit for others' work Nature Portfolio journals' policy on duplicate publication Nature Portfolio journals' editorials Plagiarism and ...

arXiv Dataset Graph Representation This project builds a graph-based representation of research papers in the field of Artificial Intelligence using metadata from the official arXiv dataset. The ...