IEEE

Uncertainty Quantification for Traffic Forecasting Using Deep-Ensemble-Based Spatiotemporal Graph Neural Networks

Abstract: Deep-learning-based data-driven forecasting methods have achieved impressive results for traffic forecasting. Specifically, spatiotemporal graph neural networks have emerged as a promising ...
Journal of Medical Internet Research

Large Language Model–Driven Knowledge Graph Construction in Sepsis Care Using Multicenter Clinical Databases: Development and Usability Study

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, ...
Wall Street Journal

We’re Using So Much AI That Computing Firepower Is Running Out

What really happens after you hit enter on that AI prompt? WSJ’s Joanna Stern heads inside a data center to trace the journey and then grills up some steaks to show just how much energy it takes to ...
IEEE

Efficient Large Graph Partitioning Scheme Using Incremental Processing in GPU

Abstract: As the processing of large-scale graphs on a single device is infeasible without partitioning, graph partitioning algorithms are essential for various algorithms and distributed computing ...