Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...

As one of the most crucial topics in the recommendation system field, Point-of-Interest (POI) recommendation aims to recommending potential interesting POIs to users. Recently, graph neural networks ...

Graph machine learning (or graph model), represented by graph neural networks, employs machine learning (especially deep learning) to graph data and is an important research direction in the ...

The Optum Enterprise and Data Analytics (EDA) Graph & Health @ Scale (GHS) team is happy to announce v1.0 of our g2gnn library. In this presentation we will discuss the g2gnn library, how it works, ...

A key lesson was to measure what matters. From the outset, we defined clear success metrics—latency reduction, resource efficiency and cost improvement.