As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

Abstract: Gene-gene association studies are essential for genomic analysis in network medicine. Multi-omics datasets of multiple disease phenotypes are used to construct a disease-gene network or ...

This page assumes you are already familiar with the content of Introduction to visualization; in particular, you should already understand the sequence graph representation used. Right now you may be ...

Fifteen years ago, I introduced the zero-trust security model while working as an analyst at Forrester Research. At the time, cybersecurity was still rooted in perimeter-based thinking, built on the ...

Rons Data Streamer is a powerful network monitoring tool for real-time traffic analysis. Capture, visualize. Rons Data Streamer is a sophisticated and user-friendly software application designed for ...

Instant experiences on the web have become more of a requirement than a preference. The performance of React applications depends heavily on JavaScript bundle size ...

Extreme Networks has fully launched its Extreme Platform One, an agentic AI-focused network visualization offering. Revealed back in February, the platform is now generally available, with the vendor ...

Imagine standing atop a mountain, gazing at the vast landscape below, trying to make sense of the world around you. For centuries, explorers relied on such vantage points to map their surroundings.

Abstract: Graph visualization techniques provide a foundational framework for offering comprehensive overviews and insights into cloud computing systems, facilitating efficient management and ensuring ...

BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...