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.

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 ...

The enterprise knowledge graph is a knowledge representation system based on graph structures. It integrates multi-source data from both internal and external sources (such as business information, ...

Paramjit S. Gill, Tim B. Swartz, Bayesian Analysis of Directed Graphs Data with Applications to Social Networks, Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 53, No. 2 ...

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 ...

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 ...

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.

Siren promises the benefits of knowledge graphs, without the hassle of reinventing your existing data management and infrastructure ...