Abstract: Deep graph contrastive clustering has attracted widespread attentions due to its self-supervised representation learning paradigm and superior clustering performance. Although, two ...

Abstract: High renewable penetration and reduced system inertia introduce significant challenges for transient stability assessment and control. This article proposes a causality-aware, large language ...

Conclusions: This study represents a pioneering effort in using LLMs, particularly GPT-4.0, to construct a comprehensive sepsis knowledge graph. The innovative application of prompt engineering, ...

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...