As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

Abstract: Dynamic graphs (DGs), which capture time-evolving relationships between graph entities, have widespread real-world applications. To efficiently encode DGs for downstream tasks, most DG ...

1 Guangdong Power Grid Corporation Foshan Power Supply Bureau, Foshan, China 2 Electric Power Research Institute of China Southern Power Grid, Guangzhou, Guangdong, China Introduction: The escalating ...

financial-dynamic-knowledge-graph/ ├── main.py # Main training script ├── report.md # Full project report (blog post format) ├── requirements.txt # Python dependencies │ ├── src/ │ ├── models/ │ │ ├── ...

QUEEN (QUantized Efficient ENcoding) is a novel framework for efficient, streamable free-viewpoint video (FVV) representation using dynamic 3D Gaussians. QUEEN enables high-quality dynamic scene ...

The reorganization reflects the ongoing shift in the federal government’s energy priorities: less renewable energy, more fossil fuels. By Brad Plumer Reporting from Washington The Energy Department is ...

You could argue that Sayin had an OK day on Saturday in West Lafayette. Yet, the redshirt freshman completed 82% of his passes and threw for over 300 yards, the type of efficiency and yardage that has ...

The prediction of the properties of crystal materials has always been a core issue in materials science and solid-state physics. With the rapid development of computer simulation techniques and ...

For much of the last half century, static efficiency has been posited to be in tension with dynamic efficiency. Theorists such as Schumpeter and Williamson introduced models suggesting that firms ...