François Théberge

Proceedings of the Modelling and Mining Networks - 19th International Workshop, 2024

2023

Artificial benchmark for community detection with outliers (ABCD+o).

[BibT_eX]

[DOI]

Appl. Netw. Sci., December, 2023

Hypergraph Artificial Benchmark for Community Detection (h-ABCD).

[BibT_eX]

[DOI]

Arash Dehghan-Kooshkghazi

J. Complex Networks, June, 2023

Generative Methods for Social Media Analysis

[BibT_eX]

[DOI]

Springer Briefs in Computer Science, Springer, ISBN: 978-3-031-33616-4, 2023

Classification Supported by Community-Aware Node Features.

[BibT_eX]

[DOI]

Proceedings of the Complex Networks & Their Applications XII, 2023

2022

A multi-purposed unsupervised framework for comparing embeddings of undirected and directed graphs.

[BibT_eX]

[DOI]

Netw. Sci., December, 2022

Modularity of the ABCD random graph model with community structure.

[BibT_eX]

[DOI]

J. Complex Networks, October, 2022

Evaluating node embeddings of complex networks.

[BibT_eX]

[DOI]

J. Complex Networks, June, 2022

Properties and Performance of the ABCDe Random Graph Model with Community Structure.

[BibT_eX]

[DOI]

Big Data Res., 2022

Outliers in the ABCD Random Graph Model with Community Structure (ABCD+o).

[BibT_eX]

[DOI]

Proceedings of the Complex Networks and Their Applications XI, 2022

2021

Comparing Graph Clusterings: Set Partition Measures vs. Graph-Aware Measures.

[BibT_eX]

[DOI]

Valérie Poulin

IEEE Trans. Pattern Anal. Mach. Intell., 2021

Artificial Benchmark for Community Detection (ABCD) - Fast random graph model with community structure.

[BibT_eX]

[DOI]

Netw. Sci., 2021

Survey of Generative Methods for Social Media Analysis.

[BibT_eX]

[DOI]

CoRR, 2021

An unsupervised framework for comparing graph embeddings.

[BibT_eX]

[DOI]

J. Complex Networks, 2021

2020

A Scalable Unsupervised Framework for Comparing Graph Embeddings.

[BibT_eX]

[DOI]

Proceedings of the Algorithms and Models for the Web Graph - 17th International Workshop, 2020

Community Detection Algorithm Using Hypergraph Modularity.

[BibT_eX]

[DOI]

Proceedings of the Complex Networks & Their Applications IX, 2020

2019

Ensemble clustering for graphs: comparisons and applications.

[BibT_eX]

[DOI]

Valérie Poulin

Appl. Netw. Sci., 2019

2018

Ensemble Clustering for Graphs.

[BibT_eX]

[DOI]

Valérie Poulin

Proceedings of the Complex Networks and Their Applications VII, 2018

2003

Almost all complete binary prefix codes have a self-synchronizing string.

[BibT_eX]

[DOI]

Christopher F. Freiling

Douglas S. Jungreis

Kenneth Zeger

IEEE Trans. Inf. Theory, 2003

1998

Upper bounds for blocking probabilities in large multi-rate loss networks.

[BibT_eX]

[DOI]

Alain Simonian

Ravi Mazumdar

Telecommun. Syst., 1998

1997

Calculating Cell Loss Probabilities for ON-OFF Sources in Large Unbuffered Systems.

[BibT_eX]

[DOI]

Nikolay B. Likhanov

Ravi Mazumdar

Proceedings of the 1997 IEEE International Conference on Communications: Towards the Knowledge Millennium, 1997

1995

Approximation Formulae for Blocking Probabilities in a Large Erlang Loss System: A Probabilistic Approach.

[BibT_eX]