4 citations · 5 across the 5 of their papers we have counts for
6 papers
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…
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…
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…
Markov processes on quasi-random graphs
Dániel Keliger
We study Markov population processes on large graphs, with the local state transition rates of a single vertex being linear function of its neighborhood. A simple way to approximat…
Local-density dependent Markov processes on graphons with epidemiological applications
Daniel Keliger, Illes Horvath, Balint Takacs
We investigate local-density dependent Markov processes on a class of large graphs sampled from a graphon, where the transition rates of the vertices are influenced by the states o…
Mean field limit of local density-dependent Markov processes on weighted Erdos-Renyi graphs
Daniel Keliger, Illes Horvath
We study the asymptotic behaviour of Markov processes on large weighted Erdos-Renyi graphs where the transition rates of the vertices are only influenced by the state of their neig…