2 papers
cs.LG2020
FiGLearn: Filter and Graph Learning using Optimal Transport
Matthias Minder, Zahra Farsijani, Dhruti Shah +2
In many applications, a dataset can be considered as a set of observed signals that live on an unknown underlying graph structure. Some of these signals may be seen as white noise…
cs.LG2020
Wasserstein-based Graph Alignment
Hermina Petric Maretic, Mireille El Gheche, Matthias Minder +2
We propose a novel method for comparing non-aligned graphs of different sizes, based on the Wasserstein distance between graph signal distributions induced by the respective graph…