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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…

math.PR2025

Polymer Dynamics via Cliques: New Conditions for Approximations

Tobias Friedrich, Andreas Göbel, Martin S. Krejca +1

Abstract polymer models are systems of weighted objects, called polymers, equipped with an incompatibility relation. An important quantity associated with such models is the partit…

math.PR2025

Gradually Declining Immunity Retains the Exponential Duration of Immunity-Free Diffusion

Andreas Göbel, Nicolas Klodt, Martin S. Krejca +1

Diffusion processes pervade numerous areas of AI, abstractly modeling the dynamics of exchanging, oftentimes volatile, information in networks. A central question is how long the i…

math.PR2024

From Market Saturation to Social Reinforcement: Understanding the Impact of Non-Linearity in Information Diffusion Models

Tobias Friedrich, Andreas Göbel, Nicolas Klodt +2

Diffusion of information in networks is at the core of many problems in AI. Common examples include the spread of ideas and rumors as well as marketing campaigns. Typically, inform…