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pro vyhledávání: '"Thomas, Josephine Maria"'
Autor:
Beddar-Wiesing, Silvia, D'Inverno, Giuseppe Alessio, Graziani, Caterina, Lachi, Veronica, Moallemy-Oureh, Alice, Scarselli, Franco, Thomas, Josephine Maria
Graph Neural Networks (GNNs) are a large class of relational models for graph processing. Recent theoretical studies on the expressive power of GNNs have focused on two issues. On the one hand, it has been proven that GNNs are as powerful as the Weis
Externí odkaz:
http://arxiv.org/abs/2210.03990
Autor:
Beddar-Wiesing, Silvia, D’Inverno, Giuseppe Alessio, Graziani, Caterina, Lachi, Veronica, Moallemy-Oureh, Alice, Scarselli, Franco, Thomas, Josephine Maria
Publikováno v:
In Neural Networks May 2024 173
Autor:
Thomas, Josephine Maria, Muscoloni, Alessandro, Ciucci, Sara, Bianconi, Ginestra, Cannistraci, Carlo Vittorio
Publikováno v:
Nature Communications 8, 1615 (2017)
Complex network topologies and hyperbolic geometry seem specularly connected, and one of the most fascinating and challenging problems of recent complex network theory is to map a given network to its hyperbolic space. The Popularity Similarity Optim
Externí odkaz:
http://arxiv.org/abs/1602.06522
Publikováno v:
2015, New Journal of Physics, 17, 113037
Bipartite networks are powerful descriptions of complex systems characterized by two different classes of nodes and connections allowed only across but not within the two classes. Surprisingly, current complex network theory presents a theoretical bo
Externí odkaz:
http://arxiv.org/abs/1504.07011
Autor:
Beddar-Wiesing, Silvia, D'Inverno, Giuseppe Alessio, Graziani, Caterina, Lachi, Veronica, Moallemy-Oureh, Alice, Scarselli, Franco, Thomas, Josephine Maria
Graph Neural Networks (GNNs) are a large class of relational models for graph processing. Recent theoretical studies on the expressive power of GNNs have focused on two issues. On the one hand, it has been proven that GNNs are as powerful as the Weis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::470d2c9b81520fcfb960111709a3f4a6
https://doi.org/10.2139/ssrn.4415799
https://doi.org/10.2139/ssrn.4415799
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