Abstract: Graph theory and machine learning are revolutionary approaches to medical image analysis that leverage the structural nuances of medical data for better diagnostic accuracy. This research ...

Preface: mcp-agent-graph is an efficient, lightweight, and easy-to-use Agent development framework. As an Agent developer, you might use visual workflow orchestration tools like Dify or Coze; you ...

We aim to build a pre-trained Graph Neural Network (GNN) model on molecules without human annotations or prior knowledge. Although various attempts have been proposed to overcome limitations in ...

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 ...

The graph database market, driven by AI, is growing at a rate of almost 25% annually. Graph databases support knowledge graphs, providing visual guidance for AI development. There are multiple ...

Abstract: Multiview graph clustering (MGC) methods are increasingly being studied due to the explosion of multiview data with graph structural information. The critical point of MGC is to better ...