Network Science and AI
07.02.2025Over the past two decades. network science has developed statistical methods to analyze and model patterns in complex networks. Similarly, the deep learning community has recently developed new approaches to generalize neural network architectures to graph-structured data. Unfortunately, there are few interactions between these two communities. In a new preprint, we highlight challenges of opportunites at the intersection between network science and deep graph learning.
Over the past two decades. network science has developed statistical methods to analyze and model patterns in complex networks. Similarly, the deep learning community has recently developed new approaches to generalize neural network architectures to graph-structured data. Unfortunately, there are few interactions between these two communities. In a new preprint, we highlight challenges of opportunites at the intersection between network science and deep graph learning.
The preprint is available at https://arxiv.org/abs/2502.01177
