10 citations · 12 across the 3 of their papers we have counts for
4 papers
Local2Global: A distributed approach for scaling representation learning on graphs
Lucas G. S. Jeub, Giovanni Colavizza, Xiaowen Dong +2
We propose a decentralised "local2global"' approach to graph representation learning, that one can a-priori use to scale any embedding technique. Our local2global approach proceeds…
Local2Global: Scaling global representation learning on graphs via local training
Lucas G. S. Jeub, Giovanni Colavizza, Xiaowen Dong +2
We propose a decentralised "local2global" approach to graph representation learning, that one can a-priori use to scale any embedding technique. Our local2global approach proceeds…
Weight Thresholding on Complex Networks
Xiaoran Yan, Lucas G. S. Jeub, Alessandro Flammini +2
Weight thresholding is a simple technique that aims at reducing the number of edges in weighted networks that are otherwise too dense for the application of standard graph theoreti…
Multiresolution Consensus Clustering in Networks
Lucas G. S. Jeub, Olaf Sporns, Santo Fortunato
Networks often exhibit structure at disparate scales. We propose a method for identifying community structure at different scales based on multiresolution modularity and consensus…