activity
20172026
most citedBeing an Influencer is Hard: The Complexity of Influence Maximization in Temporal Graphs with a Fixed Source

1 citations · 2 across the 19 of their papers we have counts for

collaborators

21 papers

cs.DS2026

Reconfiguration of Temporal Networks under Reachability Constraints

Othon Michail, George Skretas, Georg Tennigkeit +1

Temporal networks model dynamic systems in which edges represent interactions and labels specify when these interactions occur. Examples include transportation networks, time-sensi…

cs.DC2026

Distributed Symmetry Breaking on Hyperbolic Random Graphs

Yannic Maus, Janosch Ruff, Sonia Simons +1

Real-world networks like the internet share patterns like a power law degree distribution and a high clustering coefficient. Many of these properties are captured by the generative…

cs.DS2026

Maximizing Reachability via Shifting of Temporal Paths

Argyrios Deligkas, Michelle Döring, Eduard Eiben +2

We examine the problem of maximizing the reachability of a given source in temporal graphs that are given as the union of k temporal paths, i.e., every given path is a sequence of…

cs.DS2026

Temporal Routing in Static Networks: The Schedule Completion Problem

Michelle Döring, Niklas Mohrin, George Skretas

We introduce the Temporally Edge Disjoint Schedule Completion (TEDSC) problem in which we need to cover a set of temporal edge demands by routing temporal walks through a d…

cs.GT2026

Temporal Network Creation Games: The Impact of Flexible Labels

Hans Gawendowicz, Nicolas Klodt, Aleksandrs Morgensterns +1

A crucial aspect of research is understanding how real-world networks, such as transportation and information networks, are formed. A prominent model for such networks was introduc…

cs.DM2026

FO and MSO Model Checking on Temporal Graphs

Michelle Döring, Jessica Enright, Laura Larios-Jones +1

Algorithmic meta-theorems provide an important tool for showing tractability of graph problems on graph classes defined by structural restrictions. While such results are well esta…

cs.DS2025

Parameterized Complexity of Temporal Connected Components

Argyrios Deligkas, Michelle Döring, Eduard Eiben +3

We study the parameterized complexity of maximum temporal connected components (tccs) in temporal graphs, that is, graphs whose edges are available only at specific points in time.…

cs.DS2025

Temporal Graph Reconfiguration for Always-Connected Graphs

Paul Sievers, George Skretas, Georg Tennigkeit

Network redesign problems ask for modifications to the edges of a given graph to satisfy certain properties. In temporal graphs, where edges are only active at certain times, we ar…

cs.DM2025

Temporal Exploration of Random Spanning Tree Models

Samuel Baguley, Andreas Göbel, Nicolas Klodt +3

The Temporal Graph Exploration problem (TEXP) takes as input a temporal graph, i.e., a sequence of graphs on the same vertex set, and asks for a walk of s…

cs.DS2024

Dynamic Network Discovery via Infection Tracing

Ben Bals, Michelle Döring, Nicolas Klodt +1

Researchers, policy makers, and engineers need to make sense of data from spreading processes as diverse as rumor spreading in social networks, viral infections, and water contamin…

cs.DS2024

Catch Me If You Can: Finding the Source of Infections in Temporal Networks

Ben Bals, Michelle Döring, Nicolas Klodt +1

Source detection (SD) is the task of finding the origin of a spreading process in a network. Algorithms for SD help us combat diseases, misinformation, pollution, and more, and hav…

cs.GT2024

Temporal Network Creation Games: The Impact of Non-Locality and Terminals

Davide Bilò, Sarel Cohen, Tobias Friedrich +4

We live in a world full of networks where our economy, our communication, and even our social life crucially depends on them. These networks typically emerge from the interaction o…

cs.DS2024

Hyperbolic Random Graphs: Clique Number and Degeneracy with Implications for Colouring

Samuel Baguley, Yannic Maus, Janosch Ruff +1

Hyperbolic random graphs inherit many properties that are present in real-world networks. The hyperbolic geometry imposes a scale-free network with a strong clustering coefficient.…

cs.SI2024

How Many Lines to Paint the City: Exact Edge-Cover in Temporal Graphs

Argyrios Deligkas, Michelle Döring, Eduard Eiben +3

Logistics and transportation networks require a large amount of resources to realize necessary connections between locations and minimizing these resources is a vital aspect of pla…

cs.DM2024

How to Reduce Temporal Cliques to Find Sparse Spanners

Sebastian Angrick, Ben Bals, Tobias Friedrich +7

Many real-world networks, such as transportation or trade networks, are dynamic in the sense that the edge set may change over time, but these changes are known in advance. This be…

cs.GT2023

Temporal Network Creation Games

Davide Bilò, Sarel Cohen, Tobias Friedrich +4

Most networks are not static objects, but instead they change over time. This observation has sparked rigorous research on temporal graphs within the last years. In temporal graphs…

cs.CC2023★ 1 cited

Being an Influencer is Hard: The Complexity of Influence Maximization in Temporal Graphs with a Fixed Source

Argyrios Deligkas, Michelle Döring, Eduard Eiben +2

We consider the influence maximization problem over a temporal graph, where there is a single fixed source. We deviate from the standard model of influence maximization, where the…

cs.DS2021

Minimizing Reachability Times on Temporal Graphs via Shifting Labels

Argyrios Deligkas, Eduard Eiben, George Skretas

We study how we can accelerate the spreading of information in temporal graphs via shifting operations; a problem that captures real-world applications varying from information flo…

cs.DS2021

The Complexity of Growing a Graph

George B. Mertzios, Othon Michail, George Skretas +2

We study a new algorithmic process of graph growth which starts from a single initial vertex and operates in discrete time-steps, called \emph{slots}. In every slot, the graph grow…

cs.DC2020

Distributed Computation and Reconfiguration in Actively Dynamic Networks

Othon Michail, George Skretas, Paul G. Spirakis

In this paper, we study systems of distributed entities that can actively modify their communication network. This gives rise to distributed algorithms that apart from communicatio…

cs.DS2017★ 1 cited

On the Transformation Capability of Feasible Mechanisms for Programmable Matter

Othon Michail, George Skretas, Paul G. Spirakis

In this work, we study theoretical models of \emph{programmable matter} systems. The systems under consideration consist of spherical modules, kept together by magnetic forces and…