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math.PR2025
Accuracy criterion for mean field approximations of Markov processes on hypergraphs
Illes Horvath, Daniel Keliger
We provide error bounds for the N-intertwined mean-field approximation (NIMFA) for local density-dependent Markov population processes with a well-distributed underlying network st…
math.PR2025
The effects of initial conditions on the accuracy of mean-field approximations of Markov processes on large random graphs
Pierfrancesco Dionigi, Dániel Keliger
We study the evolution of a general class of stochastic processes (containing, e.g. SIS and SIR models) on large random networks, focusing on a particular general class of random g…
math.PR2024
Concentration and mean field approximation results for Markov processes on large networks
Dániel Keliger, Balázs Ráth
We study Markov processes on weighted directed hypergraphs where the state of at most one vertex can change at a time. Our setting is general enough to include simplicial epidemic…