Many middle school math students stumble over a deceptively simple question: What does a negative slope actually mean? By inviting students to not just see a line but hear it, teachers can help ...

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 ...

We therefore argue for an expanded power lens in implementation science—one that brings into view the multiple and intersecting forms of power that shape what gets implemented, by whom, and for whose ...

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: An undirected weighted graph (UWG) is the fundamental data representation in various real applications. A graph convolution network is frequently utilized for representation learning to a ...

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 ...

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 ...