This is our PyTorch implementation of EPAGCL: Yanchen Xu +, Siqi Huang +, Hongyuan Zhang *, and Xuelong Li *, "Why Does Dropping Edges Usually Outperform Adding Edges in Graph Contrastive Learning?", ...

For a long time, companies have been using relational databases (DB) to manage data. However, with the increasing use of ...

Abstract: Detecting fraud in multi-relational graphs is a significant difficulty due to the complex nature of fraudulent activities and the inadequacies of conventional Graph Neural Networks (GNNs) in ...

Abstract: Task offloading in mobile edge computing (MEC) becomes particularly challenging when dealing with complex, interdependent subtasks, especially under dynamic network conditions and resource ...

The latest information from the National Intellectual Property Administration shows that Shengdi Xingtou Information ...

Understand the merits of large language models vs. small language models, and why knowledge graphs are the missing piece 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 ...

While you might think tariffs and competition are weighing Ford down, this is really what's causing a disaster.

This is the official companion repository for the book The Complete LangGraph Blueprint: Build 50+ AI Agents for Business Success. The repository provides source code, practical examples, and ...

Enterprise search startup Glean has attracted customers and venture capital thanks to an AI search tool that lets employees ...

A next-generation graph-relational database (DB) system has been developed in South Korea. If this system is applied in ...