46 citations · 192 across the 23 of their papers we have counts for
5 papers · 1 filter
Scikit-network: Graph Analysis in Python
Thomas Bonald, Nathan de Lara, Quentin Lutz +1
Scikit-network is a Python package inspired by scikit-learn for the analysis of large graphs. Graphs are represented by their adjacency matrix in the sparse CSR format of SciPy. Th…
Learning Graph Representations by Dendrograms
Thomas Bonald, Bertrand Charpentier
Hierarchical graph clustering is a common technique to reveal the multi-scale structure of complex networks. We propose a novel metric for assessing the quality of a hierarchical c…
Hierarchical Graph Clustering using Node Pair Sampling
Thomas Bonald, Bertrand Charpentier, Alexis Galland +1
We present a novel hierarchical graph clustering algorithm inspired by modularity-based clustering techniques. The algorithm is agglomerative and based on a simple distance between…
A linear streaming algorithm for community detection in very large networks
Alexandre Hollocou, Julien Maudet, Thomas Bonald +1
In this paper, we introduce a novel community detection algorithm in graphs, called SCoDA (Streaming Community Detection Algorithm), based on an edge streaming setting. This algori…
Improving PageRank for Local Community Detection
Alexandre Hollocou, Thomas Bonald, Marc Lelarge
Community detection is a classical problem in the field of graph mining. While most algorithms work on the entire graph, it is often interesting in practice to recover only the com…