Evidence-based Directed Acyclic Graphs (DAGs) are effective tools to comprehensively visualize complex causal and biasing pathways in pharmacoepidemiologic research in rheumatology. This paper ...

This article presents a technical implementation of Graph RAG (Retrieval-Augmented Generation) integrated with Odoo Open Source CRM platform. The implementation combines Neo4j knowledge graphs with ...

Graph theory is a foundational area of mathematics and computer science that deals with the study of graphs structures made up of nodes (also called vertices) and edges that connect pairs of nodes. In ...

Genomic medicine relies on single reference genomes that miss crucial genetic diversity, creating diagnostic gaps that disproportionately affect underrepresented populations. Pangenome graphs, ...

Abstract: This paper presents a novel approach to graph learning, GL-AR, which leverages estimated autoregressive coefficients to recover undirected graph structures from time-series graph signals ...

Graph neural networks (GNN) have achieved remarkable success in various domains, yet incomplete node attribute data can significantly impair their performance. Graph completion learning (GCL) methods ...

Abstract: Collaborative analysis on graph data from diverse sources has shown great promise in finance, social networking, and predictive modeling. However, efficiently collaborative graph-data ...

Check approxCCDegree.cpp for the code, and sample.cpp for a sample implementation. Let n u be the number of nodes in the connected component where the node u is located. The number of connected ...

Microsoft announced during its Build 2025 keynote that it will open source GitHub Copilot in Visual Studio Code, its lightweight, cross-platform code editor, while adding a plethora of new features to ...