Analysis and Simulation
of Complex Networks

@article{grossmannUnsupervisedRelationalInferenceUsing2023,
 author = {Gerrit Großmann and Julian Zimmerlin and Michael Backenköhler and Verena Wolf},
 doi = {10.1007/s41109-023-00542-x},
 journal = {Applied Network Science},
 month = {4},
 number = {18},
 pages = {1-21},
 publisher = {Springer},
 title = {Unsupervised relational inference using masked reconstruction},
 url = {https://appliednetsci.springeropen.com/articles/10.1007/s41109-023-00542-x},
 volume = {8},
 year = {2023}
}

@article{grossmannHeterogeneityMattersContactStructure2021,
 author = {Gerrit Großmann and Michael Backenköhler and Verena Wolf},
 doi = {10.1371/journal.pone.0250050},
 editor = {Vygintas Gontis},
 journal = {PLOS One},
 month = {7},
 number = {7},
 pages = {1-19},
 publisher = {Public Library of Science},
 title = {Heterogeneity matters: Contact structure and individual variation shape epidemic dynamics},
 volume = {16},
 year = {2021}
}

@inproceedings{grossmannEpidemicOverdispersionStrengthensThe2021,
 author = {Gerrit Großmann and Michael Backenköhler and Verena Wolf},
 booktitle = {HSCC '21: Proceedings of the 24th International Conference on Hybrid Systems: Computation and Control. ACM International Conference on Hybrid Systems: Computation and Control (HSCC-2021), May 19-21, Nashville,, Tennesse, USA},
 doi = {10.1145/3447928.3457209},
 isbn = {978-1-4503-8339-4},
 month = {5},
 pages = {1-3},
 publisher = {ACM, New York, NY},
 title = {Epidemic overdispersion strengthens the effectiveness of mobility restrictions},
 year = {2021}
}

@inproceedings{grossmannLearningVaccineAllocationFrom2020,
 author = {Gerrit Großmann and Michael Backenköhler and Jonas Klesen and Verena Wolf},
 booktitle = {Complex Networks & Their Applications IX. International Conference on Complex Networks and their Applications (COMPLEX NETWORKS-2020), Proceedings of the Ninth International Conference on Complex Networks and Their Applications, December 1-3, Madrid, Spain},
 doi = {10.1007/978-3-030-65347-7_36},
 editor = {Rosa M. Benito and Chantal Cherifi and Hocine Cherifi and Esteban Moro and Luis Aurelio Rocha and Marta Sales-Pardo},
 isbn = {9783030653477},
 month = {12},
 pages = {432-443},
 publisher = {Springer International Publishing, Switzerland},
 title = {Learning Vaccine Allocation from Simulations},
 volume = {1},
 year = {2020}
}

@article{grossmannEfficientSimulationOfNonMarkovian2020,
 author = {Gerrit Großmann and Luca Bortolussi and Verena Wolf},
 doi = {10.1371/journal.pone.0241394},
 editor = {Hocine Cherifi},
 journal = {PLOS ONE},
 month = {10},
 number = {10},
 pages = {1-18},
 publisher = {PLOS ONE},
 title = {Efficient simulation of non-Markovian dynamics on complex networks},
 volume = {15},
 year = {2020}
}

@inproceedings{grossmannImportanceOfInteractionStructure2020,
 author = {Gerrit Großmann and Michael Backenköhler and Verena Wolf},
 booktitle = {Quantitative Evaluation of Systems. International Conference on Quantitative Evaluation of Systems (QEST-2020), 17th International Conference, QEST 2020, October 31 - September 1, Vienna, Austria},
 doi = {10.1007/978-3-030-59854-9_16},
 edition = {1st},
 editor = {Marco Gribaudo and David N. Jansen and Anne Remke},
 isbn = {9783030598549},
 month = {9},
 pages = {211-229},
 publisher = {Springer International Publishing, Switzerland},
 title = {Importance of Interaction Structure and Stochasticity for Epidemic Spreading: A COVID-19 Case Study},
 volume = {12289},
 year = {2020}
}

@inproceedings{grossmannRejectionBasedSimulationOfNonMarkovian2020,
 address = {Cham},
 author = {Großmann, Gerrit and Bortolussi, Luca and Wolf, Verena},
 booktitle = {Complex Networks and Their Applications VIII},
 editor = {Cherifi, Hocine and Gaito, Sabrina and Mendes, José Fernendo and Moro, Esteban and Rocha, Luis Mateus},
 isbn = {978-3-030-36687-2},
 pages = {349--361},
 publisher = {Springer International Publishing},
 title = {Rejection-Based Simulation of Non-Markovian Agents on Complex Networks},
 year = {2020}
}

@article{backenkohlerPosterAbstractBirthDeathProcesses2020,
 author = {Backenköhler, Michael and Grossmann, Gerrit},
 month = {01},
 pages = {},
 title = {Poster Abstract: Birth-Death Processes Reproduce the Infection Footprint of Complex Networks},
 year = {2020}
}

@inproceedings{grossmannRejectionBasedSimulationOfStochastic2019,
 author = {Gerrit Großmann and Verena Wolf},
 booktitle = {Hybrid Systems Biology - 6th International Workshop, Revised Selected Papers. International Workshop on Hybrid Systems Biology (HSB-2019), April 6-7, Prague, Czech Republic},
 doi = {10.1007/978-3-030-28042-0_5},
 editor = {Milan Češka and Nicola Paoletti},
 isbn = {978-3-030-28041-3},
 month = {8},
 pages = {63-79},
 publisher = {Springer Nature},
 series = {Lecture Notes in Bioinformatics, LNBI},
 title = {Rejection-Based Simulation of Stochastic Spreading Processes on Complex},
 volume = {11705},
 year = {2019}
}

@inproceedings{grossmannReducingSpreadingProcessesOn2019,
 address = {Cham},
 author = {Großmann, Gerrit and Bortolussi, Luca},
 booktitle = {Quantitative Evaluation of Systems},
 editor = {Parker, David and Wolf, Verena},
 isbn = {978-3-030-30281-8},
 pages = {292--309},
 publisher = {Springer International Publishing},
 title = {Reducing Spreading Processes on Networks to Markov Population Models},
 year = {2019}
}

@article{kyriakopoulosLumpingOfDegreeBasedMeanField2018,
$ of the network, which is much smaller than the size of the master equation of the underlying stochastic model, yet numerically solving these equations can still be problematic for large $k_{\max}$. In this paper, we consider AME and PA, extended to cope with multiple local states, and we provide an aggregation procedure that clusters together nodes having similar degrees, treating those in the same cluster as indistinguishable, thus reducing the number of equations while preserving an accurate description of global observables of interest. We also provide an automatic way to build such equations and to identify a small number of degree clusters that give accurate results. The method is tested on several case studies, where it shows a high level of compression and a reduction of computational time of several orders of magnitude for large networks, with minimal loss in accuracy},
 author = {Kyriakopoulos, Charalampos and Grossmann, Gerrit and Wolf, Verena and Bortolussi, Luca},
 doi = {10.1103/PhysRevE.97.012301},
 issue = {1},
 journal = {Phys. Rev. E},
 month = {Jan},
 numpages = {15},
 pages = {012301},
 publisher = {American Physical Society},
 title = {Lumping of degree-based mean-field and pair-approximation equations for multistate contact processes},
 url = {https://link.aps.org/doi/10.1103/PhysRevE.97.012301},
 volume = {97},
 year = {2018}
}

@inproceedings{grossmannLumpingTheApproximateMaster2018,
 address = {Cham},
 author = {Großmann, Gerrit and Kyriakopoulos, Charalampos and Bortolussi, Luca and Wolf, Verena},
 booktitle = {Quantitative Evaluation of Systems},
 editor = {McIver, Annabelle and Horvath, Andras},
 isbn = {978-3-319-99154-2},
 pages = {157--172},
 publisher = {Springer International Publishing},
 title = {Lumping the Approximate Master Equation for Multistate Processes on Complex Networks},
 year = {2018}
}