81 citations · 88 across the 3 of their papers we have counts for
4 papers
Cup and Cap Topological Neural Network
Marta Niedostatek, Ferran Hernandez Caralt, Runyue Wang +4
Topological Deep Learning (TDL) is designed to learn features associated with higher-dimensional simplices including not only nodes but also edges, triangles and so on. However, mo…
ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain
Guillermo Bernárdez, Lev Telyatnikov, Marco Montagna +70
This paper describes the 2nd edition of the ICML Topological Deep Learning Challenge that was hosted within the ICML 2024 ELLIS Workshop on Geometry-grounded Representation Learnin…
Similarity matrix average for aggregating multiplex networks
Federica Baccini, Lucio Barabesi, Eugenio Petrovich
We introduce a methodology based on averaging similarity matrices with the aim of integrating the layers of a multiplex network into a single monoplex network. Multiplex networks a…
Weighted simplicial complexes and their representation power of higher-order network data and topology
Federica Baccini, Filippo Geraci, Ginestra Bianconi
Hypergraphs and simplical complexes both capture the higher-order interactions of complex systems, ranging from higher-order collaboration networks to brain networks. One open prob…