Graph-structured data are pervasive in the real-world such as social networks, molecular graphs and transaction networks.

Alongside text-based large language models (LLMs), including ChatGPT in industrial fields, GNN (Graph Neural Network)-based graph AI models that analyze unstructured data such as financial ...

“Graph neural networks, or GNNs for short, have emerged as a powerful technique to leverage both the graph’s connectivity (as in the older algorithms DeepWalk and Node2Vec) and the input ...

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs through graph partitioning, has been developed by researchers at ...

Alongside text-based large language models (LLMs) including ChatGPT, in industrial fields, GNN (Graph Neural Network)-based ...

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and ...

The ideas are illustrated by the graph in Figure 2. The hypothetical graph shows a linear prediction system, but the ideas are the same for a neural network. There are 10 training data points. A ...