Abstract: Knowledge Graph Completion (KGC) has garnered massive research interest recently, and most existing methods are designed following a transductive setting where all entities are observed ...

We aim to build a pre-trained Graph Neural Network (GNN) model on molecules without human annotations or prior knowledge. Although various attempts have been proposed to overcome limitations in ...

Based on InfraNodus AI text analysis and visualization tool, this plugin visualizes the content of Obsidian vaults as a knowledge graph, retrieves the main topical clusters, most important ideas, and ...

Abstract: This paper proposes a subgraph-aware classification framework that integrates efficient frequent subgraph mining with graph neural networks (GNNs) to address the limitations of existing GNNs ...

The graph database market, driven by AI, is growing at a rate of almost 25% annually. Graph databases support knowledge graphs, providing visual guidance for AI development. There are multiple ...