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mGNN: Generalizing the Graph Neural Networks to the Multilayer Case

mGNN: Generalizing the Graph Neural Networks to the Multilayer Case

21 September 2021
Marco Grassia
Manlio De Domenico
G. Mangioni
    AI4CE
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Papers citing "mGNN: Generalizing the Graph Neural Networks to the Multilayer Case"

3 / 3 papers shown
Title
Bridging the Gap between Spatial and Spectral Domains: A Unified
  Framework for Graph Neural Networks
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks
Zhiqian Chen
Fanglan Chen
Lei Zhang
Taoran Ji
Kaiqun Fu
Liang Zhao
Feng Chen
Lingfei Wu
Charu C. Aggarwal
Chang-Tien Lu
41
18
0
21 Jul 2021
Machine learning dismantling and early-warning signals of disintegration
  in complex systems
Machine learning dismantling and early-warning signals of disintegration in complex systems
Marco Grassia
Manlio De Domenico
G. Mangioni
AAML
147
85
0
07 Jan 2021
Geometric deep learning: going beyond Euclidean data
Geometric deep learning: going beyond Euclidean data
M. Bronstein
Joan Bruna
Yann LeCun
Arthur Szlam
P. Vandergheynst
GNN
259
3,239
0
24 Nov 2016
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