Context graphs is the new buzzword for agentic Systems of Knowledge, uncovering the key role of the tribal knowledge hidden in decision threads that inform enterprise activity.
INTRODUCTION: With the ease provided by current computational programs, medical and scientific journals use bar graphs to describe continuous data. METHODS: This manuscript discusses the inadequacy of ...
To demonstrate its value, we used graph data science and machine learning to (1) propose new therapeutic targets based on similarities of AD to Parkinson disease and (2) repurpose existing drugs that ...
This repository contains code for Talk like a Graph: Encoding Graphs for Large Language Models and Let Your Graph Do the Talking: Encoding Structured Data for LLMs. @inproceedigs{fatemi2024talk, ...
GraphStorm is an enterprise-grade graph machine learning (GML) framework designed for scalability and ease of use. It simplifies the development and deployment of GML models on industry-scale graphs ...
Abstract: Time series are the primary data type used to record dynamic system measurements and generated in great volume by both physical sensors and online processes (virtual sensors). Time series ...
Abstract: Graph neural networks (GNN) are increasingly used to classify EEG for tasks such as emotion recognition, motor imagery and neurological diseases and disorders. A wide range of methods have ...
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