Abstract: Graph neural network is a new neural network model in recent years, whose advantage lies in processing graph structure data. In the era of big data, people can collect a large amount of ...

I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful. Every data point, every observation, every piece of knowledge doesn’t exist in ...

1 COSCO Shipping Technology Co., Ltd., Shanghai, China. 2 COSCO Shipping Specialized Carriers Co., Ltd., Guangzhou, China. The cost and strict input format requirements of GraphRAG make it less ...

This article introduces a model-based design, implementation, deployment, and execution methodology, with tools supporting the systematic composition of algorithms from generic and domain-specific ...

The Graph, the decentralized indexing system that works much like Google for blockchains, has introduced a data standard for Web3. Called GRC-20, the standard would define how information is ...

Neo4j is the world's leading graph database, with native graph storage and processing.. Neo4j is the world's leading graph database, with native graph storage and processing.. Neo4j is the world's ...

The timely and accurate prediction of maize (Zea mays L.) yields prior to harvest is critical for food security and agricultural policy development. Currently, many researchers are using machine ...

Abstract: In light of the growing emphasis on the right to be forgotten of graph data, machine unlearning has been extended to unlearn the graph structures’ knowledge from graph neural networks (GNNs) ...