When Spectral Domain Meets Spatial Domain in Graph Neural Networks

Autor: Muhammet, Balcilar, Guillaume, Renton, Pierre, Héroux, Benoit, Gaüzère, Sébastien, Adam, Honeine, Paul

Publikováno v: Thirty-seventh International Conference on Machine Learning (ICML 2020)-Workshop on Graph Representation Learning and Beyond (GRL+ 2020)
Thirty-seventh International Conference on Machine Learning (ICML 2020)-Workshop on Graph Representation Learning and Beyond (GRL+ 2020), Jul 2020, Vienna, Austria

International audience; Convolutional Graph Neural Networks (Con-vGNNs) are designed either in the spectral domain or in the spatial domain. In this paper, we provide a theoretical framework to analyze these neural networks, by deriving some equivale

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::c8e772ee4bb089c1e20f45dcfbe673a9
https://hal-normandie-univ.archives-ouvertes.fr/hal-03088374