Clustering via hypergraph modularity B Kamiński, V Poulin, P Prałat, P Szufel, F Théberge PloS one 14 (11), e0224307, 2019 | 60 | 2019 |

Almost all complete binary prefix codes have a self-synchronizing string CF Freiling, DS Jungreis, F Théberge, K Zeger IEEE Transactions on Information Theory 49 (9), 2219-2225, 2003 | 35 | 2003 |

Artificial benchmark for community detection (ABCD)—fast random graph model with community structure B Kamiński, P Prałat, F Théberge Network Science 9 (2), 153-178, 2021 | 22 | 2021 |

Asymptotic estimates for blocking probabilities in a large multi-rate loss network A Simonian, JW Roberts, F Theberge, R Mazumdar Advances in Applied Probability 29 (3), 806-829, 1997 | 21 | 1997 |

Ensemble clustering for graphs V Poulin, F Théberge Complex Networks and Their Applications VII: Volume 1 Proceedings The 7th …, 2019 | 20 | 2019 |

Mining complex networks B Kaminski, P Prałat, F Théberge CRC Press, 2021 | 17 | 2021 |

Community detection algorithm using hypergraph modularity B Kamiński, P Prałat, F Théberge Complex Networks & Their Applications IX: Volume 1, Proceedings of the Ninth …, 2021 | 17 | 2021 |

An unsupervised framework for comparing graph embeddings B Kamiński, P Prałat, F Théberge Journal of Complex Networks 8 (5), cnz043, 2020 | 16 | 2020 |

Ensemble clustering for graphs: comparisons and applications V Poulin, F Théberge Applied Network Science 4 (1), 51, 2019 | 14 | 2019 |

Evaluating node embeddings of complex networks A Dehghan-Kooshkghazi, B Kamiński, Ł Kraiński, P Prałat, F Théberge Journal of Complex Networks 10 (4), cnac030, 2022 | 9 | 2022 |

Providing QoS in large networks: Statistical multiplexing and admission control NB Likhanov, RR Mazumdar, F Theberge Analysis, Control and Optimization of Complex Dynamic Systems, 137-167, 2005 | 9 | 2005 |

New reduced load heuristic for computing blocking in large multirate loss networks F Theberge, RR Mazumdar IEE Proceedings-Communications 143 (4), 206-211, 1996 | 8 | 1996 |

Approximation formulae for blocking probabilities in a large Erlang loss system: a probabilistic approach F Theberge, RR Mazumdar Proceedings of INFOCOM'95 2, 804-809, 1995 | 8 | 1995 |

Modularity of the ABCD random graph model with community structure B Kamiński, B Pankratz, P Prałat, F Théberge Journal of Complex Networks 10 (6), cnac050, 2022 | 7 | 2022 |

Properties and performance of the ABCDE random graph model with community structure B Kamiński, T Olczak, B Pankratz, P Prałat, F Théberge Big Data Research 30, 100348, 2022 | 7 | 2022 |

Self-synchronization of Huffman codes CF Freiling, DS Jungreis, F Théberge, K Zeger IEEE International Symposium on Information Theory, 2003. Proceedings., 49, 2003 | 7 | 2003 |

Upper bounds for blocking probabilities in large multi‐rate loss networks F Theberge, A Simonian, RR Mazumdar Telecommunication Systems 9, 23-39, 1998 | 7 | 1998 |

A scalable unsupervised framework for comparing graph embeddings B Kamiński, P Prałat, F Théberge Algorithms and Models for the Web Graph: 17th International Workshop, WAW …, 2020 | 6 | 2020 |

Outliers in the ABCD random graph model with community structure (ABCD+ O) B Kamiński, P Prałat, F Théberge Complex Networks and Their Applications XI: Proceedings of The Eleventh …, 2023 | 5 | 2023 |

Comparing graph clusterings: Set partition measures vs. graph-aware measures V Poulin, F Théberge IEEE Transactions on Pattern Analysis and Machine Intelligence 43 (6), 2127-2132, 2020 | 3 | 2020 |