Graph neural networks (GNNs) have rapidly emerged as a central methodology for analysing complex datasets presented as graphs, where entities are interconnected through diverse relationships. By ...

Researchers have proposed a Fourier graph neural network for estimating the state of health of lithium-ion batteries while simultaneously considering spatial and temporal feature relationships. The ...

Researchers have demonstrated a new training technique that significantly improves the accuracy of graph neural networks (GNNs)—AI systems used in applications from drug discovery to weather ...

From smarter chatbots to scientific breakthroughs, combining graphs with AI is unlocking new levels of reasoning and accuracy. By structuring data into nodes and relationships, these systems gain ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

Neo4j has expanded its Google Cloud integration with new features aimed at making graph-powered AI agents and analytics more accessible. Enhancements include native Neo4j AI Agent access in Gemini ...

Emergence of new applications and use cases: Neural networks are being applied to an increasingly diverse range of applications, including computer vision, natural language processing, fraud detection ...

Parth is a technology analyst and writer specializing in the comprehensive review and feature exploration of the Android ecosystem. His work focus on productivity apps and flagship devices, ...