83 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- African Institute for Mathematical SciencesZA5 papers
- Toronto Metropolitan UniversityCA5 papers
- University of OttawaCA4 papers
- University of WarsawPL4 papers
- Bialystok University of TechnologyPL2 papers
- Prince Mohammad bin Fahd UniversitySA2 papers
- University of AveiroPT2 papers
- University of LimpopoZA2 papers
- Akdeniz University HospitalTR1 paper
- Binghamton UniversityUS1 paper
- Broad InstituteUS1 paper
- Central European UniversityAT1 paper
5 papers · 1 filter
Improving community detection via community association strength scores
Jordan Barrett, Ryan DeWolfe, Bogumił Kamiński +3
Community detection methods play a central role in understanding complex networks by revealing highly connected subsets of entities. However, most community detection algorithms ge…
Artificial Benchmark for Community Detection with Outliers (ABCD+o)
Bogumił Kamiński, Paweł Prałat, François Théberge
The Artificial Benchmark for Community Detection graph (ABCD) is a random graph model with community structure and power-law distribution for both degrees and community sizes. The…
Analyzing, Exploring, and Visualizing Complex Networks via Hypergraphs using SimpleHypergraphs.jl
Alessia Antelmi, Gennaro Cordasco, Bogumił Kamiński +4
Real-world complex networks are usually being modeled as graphs. The concept of graphs assumes that the relations within the network are binary (for instance, between pairs of node…
Artificial Benchmark for Community Detection (ABCD): Fast Random Graph Model with Community Structure
Bogumił Kamiński, Paweł Prałat, François Théberge
Most of the current complex networks that are of interest to practitioners possess a certain community structure that plays an important role in understanding the properties of the…
An Unsupervised Framework for Comparing Graph Embeddings
Bogumil Kaminski, Pawel Pralat, Francois Theberge
Graph embedding is a transformation of vertices of a graph into set of vectors. Good embeddings should capture the graph topology, vertex-to-vertex relationship, and other relevant…