Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract invariant features across varied distributions, has ...

Abstract: Graph neural networks have a variety of applications in different fields of science where graph theory has its application. One of such fields is indoor localization and mapping problems.

There’s a new relationship trend flying around the algorithm. “The bird theory” has taken TikTok by storm. But what can it actually tell you about your relationship? Here's what you need to know about ...

ABSTRACT: The primary purpose of this study is to present mathematical modeling methods inspired by graph theory operations and logic as a tool to structurally analyze the socio-economic composition ...

A new MCP Server for Fabric has also been added to enable developers to connect agents to Fabric’s ecosystem to accelerate tasks, such as creating a data pipeline or notebook. Microsoft is adding two ...

Researchers have developed a new quantum theory of gravity which describes gravity in a way that's compatible with the Standard Model of particle physics, opening the door to an improved understanding ...

Introduction: Major depressive disorder with suicidal ideation (MDD/SI+) is characterized by high prevalence, high recurrence rate, high disability rate and low response rate. There is an urgent need ...

Introduction: The electronic health record (EHR) has greatly expanded healthcare communication between patients and health workers. However, the volume and complexity of EHR messages have increased ...

Knowledge graphs are reshaping how we organize and make sense of information. By connecting data points and revealing relationships between them, these powerful tools are transforming industries, from ...