An outbreak in Gaines County, Texas, where cases have now risen to 57 from 22 on February 11, has raised concerns over its ...

To address this, we propose ERFS, an efficient feature graph representation method for intrusion detection based on flow semantic correlation. This method aims to enhance the feature representation of ...

Abstract: Some current researchers attempt to extend the graph neural network (GNN) on multi-view representation learning and learn the latent structure information among the data. Generally, they ...

GCN, a groundbreaking disentangled graph convolutional network that dynamically adjusts feature channels for enhanced node ...

Our goal is to build a high-performance Knowledge Graph tailored for Large Language Models (LLMs), prioritizing exceptionally low latency to ensure fast and efficient information delivery through our ...

The film showcases the innovative work of engineers at Bell Telephone Laboratories as they explore computer graphics and its ...

The interplay between graph analytics and large language models (LLMs) represents a promising frontier for advancing ...

We are developing a more generic V2PYG framework to provide versatile capabilities for converting RTL designs into foundational graph representations, while also ...

Earth is running a fever. That's not news. What's surprising is exactly how fast its temperature is rising Analysis As you've ...

Classic Graph Convolutional Networks (GCNs) often learn node representation holistically, which would ignore the distinct impacts from different ...

Are we putting our faith in technology that we don't fully understand? A new study comes at a time when AI systems are making decisions impacting our daily lives -- from banking and healthcare to ...

One of the biggest obstacles in multi-institutional EHR research is the inconsistency in medical coding systems across ...