TigerGraph, maker of a graph analytics platform for data scientists, during its Graph & AI Summit event today introduced its TigerGraph ML (Machine Learning) Workbench, a new-gen toolkit that ...

This is accomplished via a centralized graph database that supports the single source of truth paradigm for improved cross-domain data exchange as well as integrated multi-level modeling for vertical ...

This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labeled, streaming graph data. We introduce a ...

Imagimob Studio’s Graph UX update enhances user-friendliness and brings a collection of new capabilities to the ML design process.

ABSTRACT The objective of the present work was to implement a teaching system useful in modeling and simulation of biotechnological processes. The interactive system is based on applications developed ...

This is accomplished by adapting graph theory to represent the spatial decision-making of loggers, and by implementing computational algorithms that build graphs interpretable as logging road networks ...