4 papers
BiaScope: Visual Unfairness Diagnosis for Graph Embeddings
Agapi Rissaki, Bruno Scarone, David Liu +4
The issue of bias (i.e., systematic unfairness) in machine learning models has recently attracted the attention of both researchers and practitioners. For the graph mining communit…
netrd: A library for network reconstruction and graph distances
Stefan McCabe, Leo Torres, Timothy LaRock +4
Over the last two decades, alongside the increased availability of large network datasets, we have witnessed the rapid rise of network science. For many systems, however, the data…
Network comparison and the within-ensemble graph distance
Harrison Hartle, Brennan Klein, Stefan McCabe +4
Quantifying the differences between networks is a challenging and ever-present problem in network science. In recent years a multitude of diverse, ad hoc solutions to this problem…
The emergence of informative higher scales in complex networks
Brennan Klein, Erik Hoel
The connectivity of a network contains information about the relationships between nodes, which can denote interactions, associations, or dependencies. We show that this informatio…