Probabilistic graphs and uncertain data analysis represent a rapidly evolving research domain that seeks to reconcile the inherent imprecision of real-world data with robust computational models ...

A new open-source library by Nvidia could be the secret ingredient to advancing analytics and making graph databases faster. The key: parallel processing on Nvidia GPUs.

Why is data visualization so important in statistics, anyway? Graphs and other kinds of visualizations might seem superfluous, if you’re using statistical analysis to look for patterns in a data ...

We introduce the BioMedical Evidence Graph (BMEG), a graph database and query engine for discovery and analysis of cancer biology. The BMEG is unique from other biologic data graphs in that ...

Graphs are essential because it is impossible to navigate through the ocean of unlike data available for modeling and analysis without some tools to illuminate the process.

What do you get when you combine two of the most up-and-coming paradigms in data processing -- streaming and graphs? Likely a potential game-changer, which DARPA and others are pivoting to invest in.

In Depth › Analysis and Opinion For the love of graphs Graphs are a great way of showing relationships and trends but they can mislead as often as they inform, says Dr Paul Willis.

Graph-based data models have become central to modern machine learning and artificial intelligence applications, and are now widely used by data analysts in applications as diverse as marketing to ...

The global graph analytics market in 2022 was valued at US$1.14 billion. The market value is anticipated to grow to US$6.90 billion by 2028. The market value is expected to grow at a CAGR of 34.80 ...