activity
20242026
collaborators

9 papers

math.PR2026

A Tight Epidemic Threshold for Competing Stochastic Infection Processes with Mutually Exclusive Immunity

Nicolas Klodt, Martin S. Krejca

Stochastic infection processes are continuous-time Markov chains on graphs that assign each vertex one of multiple states, such as susceptible, infected, or recovered. Depending on…

math.PR2026

Reemergence of the Epidemic Threshold in SIRS Infections on Connected Stars

Andreas Göbel, Nicolas Klodt, Martin S. Krejca

The SIRS process is a continuous-time process for how infections spread on a graph. In this model, each vertex is in one of the following three states: susceptible (to the infectio…

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.DS2025

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.DS2025

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.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…