11 citations · 13 across the 3 of their papers we have counts for
5 papers · 1 filter
Rejection-Based Simulation of Non-Markovian Agents on Complex Networks
Gerrit Großmann, Luca Bortolussi, Verena Wolf
Stochastic models in which agents interact with their neighborhood according to a network topology are a powerful modeling framework to study the emergence of complex dynamic patte…
Reducing Spreading Processes on Networks to Markov Population Models
Gerrit Großmann, Luca Bortolussi
Stochastic processes on complex networks, where each node is in one of several compartments, and neighboring nodes interact with each other, can be used to describe a variety of re…
Rejection-Based Simulation of Stochastic Spreading Processes on Complex Networks
Gerrit Großmann, Verena Wolf
Stochastic processes can model many emerging phenomena on networks, like the spread of computer viruses, rumors, or infectious diseases. Understanding the dynamics of such stochast…
Lumping the Approximate Master Equation for Multistate Processes on Complex Networks
Gerrit Großmann, Charalampos Kyriakopoulos, Luca Bortolussi +1
Complex networks play an important role in human society and in nature. Stochastic multistate processes provide a powerful framework to model a variety of emerging phenomena such a…
Lumping of Degree-Based Mean Field and Pair Approximation Equations for Multi-State Contact Processes
Charalampos Kyriakopoulos, Gerrit Grossmann, Verena Wolf +1
Contact processes form a large and highly interesting class of dynamic processes on networks, including epidemic and information spreading. While devising stochastic models of such…