Gathering events, eg, going to gyms and meetings, are ubiquitous and crucial in the
spreading phenomena, which induce higher-order interactions, and thus can be described …

Due to the continuous emergence of various social and trade networks, network influence
analysis has aroused great interest of the researchers. Based on different influence …

Computing a (short) path between two vertices is one of the most fundamental primitives in
graph algorithmics. In recent years, the study of paths in temporal graphs, that is, graphs …

Modern, inherently dynamic systems are usually characterized by a network structure which
is subject to discrete changes over time. Given a static underlying graph, a temporal graph …

We introduce a natural temporal analogue of Eulerian circuits and prove that, in contrast to
the static case, it is NP-hard to determine whether a given temporal graph is temporally …

Temporal graphs naturally model graphs whose underlying topology changes over time.
Recently, the problems Temporal Vertex Cover (or TVC) and Sliding-Window Temporal …

We investigate the computational complexity of finding temporally disjoint paths and walks in
temporal graphs. There, the edge set changes over discrete time steps. Temporal paths and …

Most transportation networks are inherently temporal: Connections (eg flights, train runs) are
only available at certain, scheduled times. When transporting passengers or commodities …

A graph is temporally connected if a strict temporal path exists from every vertex u to every
other vertex v. This paper studies temporal design problems for undirected temporally …

The betweenness centrality of a vertex v is an important centrality measure that quantifies
how many optimal paths between pairs of other vertices visit v. Computing betweenness …