In recent years, significant advances have been made in the design and analysis of fully
dynamic algorithms. However, these theoretical results have received very little attention …

Over the recent decade, much research has been conducted in the field of social networks.
The structure of these networks has been irregular, complex, and dynamic, and certain …

In complex networks, each node has some unique characteristics that define the importance
of the node based on the given application-specific context. These characteristics can be …

Graph neural networks (GNNs) are among the most powerful tools in deep learning. They
routinely solve complex problems on unstructured networks, such as node classification …

We introduce NetworKit, an open-source software package for analyzing the structure of
large complex networks. Appropriate algorithmic solutions are required to handle …

In recent years, significant advances have been made in the design and analysis of fully
dynamic algorithms. However, these theoretical results have received very little attention …

Community detection is one of the hot topics in the complex networks. It aims to find
subgraphs that are internally dense but externally sparsely connected. In this paper, a new …

ABPA Ξ A Σ (ABRAXAS): Gnostic word of mystic meaning. We present ABRA, a suite of
algorithms to compute and maintain probabilistically guaranteed high-quality …

Graphs arise naturally in numerous situations, including social graphs, transportation
graphs, web graphs, protein graphs, etc. One of the important problems in these settings is …

In Industrial Internet of Things (IIoT), sensor nodes are vulnerable to withstand node failures
due to energy exhaustion or external attacks, which leads to the low connectivity of …