Network embedding methods have been widely and successfully used in network-based
applications such as node classification and link prediction. However, an ideal network …

This qualitative study aimed to explore how universities can incorporate the Zero Trust
Security Framework to help prevent cyber-attacks. The research question asked: How have …

A robust system should perform well under random failures or targeted attacks, and
networks have been widely used to model the underlying structure of complex systems such …

Graph representation learning with the family of graph convolution networks (GCN) provides
powerful tools for prediction on graphs. As graphs grow with more edges, the GCN family …

Network representation learning has played a critical role in studying networks. One way to
study a graph is to focus on its spectrum, ie, the eigenvalue distribution of its associated …

Network visualization has played a critical role in graph analysis, as it not only presents a
big picture of a network but also helps reveal the structural information of a network. The …

Networks (or interchangeably graphs) have been ubiquitous across the globe and within
science and engineering: social networks, collaboration networks, protein-protein interaction …