54 citations · 59 across the 4 of their papers we have counts for
7 papers · 1 filter
FGOT: Graph Distances based on Filters and Optimal Transport
Hermina Petric Maretic, Mireille El Gheche, Giovanni Chierchia +1
Graph comparison deals with identifying similarities and dissimilarities between graphs. A major obstacle is the unknown alignment of graphs, as well as the lack of accurate and in…
Multilayer Graph Clustering with Optimized Node Embedding
Mireille El Gheche, Pascal Frossard
We are interested in multilayer graph clustering, which aims at dividing the graph nodes into categories or communities. To do so, we propose to learn a clustering-friendly embeddi…
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…
Multilayer Clustered Graph Learning
Mireille El Gheche, Pascal Frossard
Multilayer graphs are appealing mathematical tools for modeling multiple types of relationship in the data. In this paper, we aim at analyzing multilayer graphs by properly combini…
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…
GOT: An Optimal Transport framework for Graph comparison
Hermina Petric Maretic, Mireille EL Gheche, Giovanni Chierchia +1
We present a novel framework based on optimal transport for the challenging problem of comparing graphs. Specifically, we exploit the probabilistic distribution of smooth graph sig…
Graph heat mixture model learning
Hermina Petric Maretic, Mireille El Gheche, Pascal Frossard
Graph inference methods have recently attracted a great interest from the scientific community, due to the large value they bring in data interpretation and analysis. However, most…