A. Schematic of Heron’s two levels of operation. Left shows a Knowledge Graph made of Nodes with Names, named Parameters and named Input/Output points. Nodes are connected with links (Edges) that ...

Abstract: Graph node feature aggregation is a very common basic operation in graph data query and graph neural networks. We design three noised aggregation methods to protect the node features of the ...

Welcome to the "three.js-visual-node-editor" repository! This is a visual graph editor designed specifically for Three TSL, allowing you to create and manipulate nodes easily for your Three.js ...

Have you ever found yourself tangled in a web of overly complicated workflows in Bricksforge, struggling to keep track of what triggers what, and why? But what if there was a way to make it simpler, ...

The intersection of computational physics and machine learning has brought significant progress in understanding complex systems, particularly through neural networks. Graph neural networks (GNNs) ...

Abstract: In recent years, reconstructing features and learning node representations by graph autoencoders (GAE) have attracted much attention in deep graph node clustering. However, existing works ...

A full open source 3D graphics editor in the browser, with scene editor, coding pad, graph editor, virtual file system, and many features more.

The ability to handle large scale graph data is crucial to an increasing number of applications. Much work has been dedicated to supporting basic graph operations such as subgraph matching, ...