Temporal graphs serve as a powerful framework for representing networks whose connections evolve over time. By incorporating time‐stamped interactions, these models capture the dynamic nature of ...

Dynamic Graph Neural Networks (Dynamic GNNs) have emerged as powerful tools for modeling real-world networks with evolving topologies and node attributes over time. A survey by Professors Zhewei Wei, ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...

The Internet of the future, and particularly the , will be interlaced with millions if not billions of intelligent, dynamic, self-organizing networks. These networks will be full of elements that are ...