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Graph neural networks (GNNs) rely on graph convolutions to extract local features from network data.
On the transferability of spectral graph filters
R. Levie, E. Isufi, and G. Leus, Kutyniok · 1901
Earlier work this paper cites.
Stability properties of graph neural networks
F. Gama, J. Bruna, and A. Ribeiro · 1905
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Transferability of spectral graph convolutional neural networks
R. Levie, M. M. Bronstein, and G. Kutyniok · 1907
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Graphon control of large-scale networks of linear systems
S. Gao and P. E. Caines · 1909
Earlier work this paper cites.
Functional Analysis
P. D. Lax · 2002
Earlier work this paper cites.
L. Ruiz, L. F. O. Chamon, and A. Ribeiro · 2003
Earlier work this paper cites.
The Laplacian spectrum of large graphs sampled from graphons
R. Vizuete, F. Garin, and P. Frasca · 2004
Earlier work this paper cites.
Limits of dense graph sequences
L. Lovász and B. Szegedy · 2006
Earlier work this paper cites.
Convergent sequences of dense graphs I: Subgraph frequencies, metric properties and testing
C. Borgs, J. T. Chayes, L. Lovász, V. T. Sós, and K. Vesztergombi · 2008
Earlier work this paper cites.
Convergent sequences of dense graphs II. multiway cuts and statistical physics
C. Borgs, J. T. Chayes, L. Lovász, V. T. Sós, and K. Vesztergombi · 2012
Earlier work this paper cites.
Large networks and graph limits , volume 60
L. Lovász · 2012
Earlier work this paper cites.
Invariant scattering convolution networks
J. Bruna and S. Mallat · 2013
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Perturbation theory for linear operators , volume 132
T. Kato · 2013
Cited alongside, same era.
The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains
D. I. Shuman, S. K. Narang, P. Frossard, A. Ortega, and P. Vandergheynst · 2013
Cited alongside, same era.
Nonparametric graphon estimation
P. J. Wolfe and S. C. Olhede · 2013
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Notes on the sin 2
A. Seelmann · 2014
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Rate-optimal graphon estimation
C. Gao, Y. Lu, and H. H. e. a. Zhou · 2015
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Centrality measures for graphons: Accounting for uncertainty in networks
M. Avella-Medina, F. Parise, M. Schaub, and S. Segarra · 2018
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Convolutional neural network architectures for signals supported on graphs
F. Gama, A. G. Marques, G. Leus, and A. Ribeiro · 2018
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Neural tangent kernel: Convergence and generalization in neural networks
A. Jacot, F. Gabriel, and C. Hongler · 2018
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Graph signal processing: Overview, challenges, and applications
A. Ortega, P. Frossard, J. Kovačević, J. M. F. Moura, and P. Vandergheynst · 2018
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Rates of convergence of spectral methods for graphon estimation
J. Xu · 2018
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Stability of graph scattering transforms
F. Gama, A. Ribeiro, and J. Bruna · 2019
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Convolutional neural networks on graphs with fast localized spectral filtering
M. Defferrard, X. Bresson, and P. Vandergheynst · 2016
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The movielens datasets: History and context
F. M. Harper and J. A. Konstan · 2016
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Geometric deep learning: Going beyond euclidean data
M. M. Bronstein, J. Bruna, Y. LeCun, A. Szlam, and P. Vandergheynst · 2017
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Semi-supervised classification with graph convolutional networks
T. N. Kipf and M. Welling · 2017
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Signal processing on kernel-based random graphs
M. W. Morency and G. Leus · 2017
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Graphon games
F. Parise and A. Ozdaglar · 2019
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Invariance-preserving localized activation functions for graph neural networks
L. Ruiz, F. Gama, G. Marques, and A. Ribeiro · 2019
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Convergence and stability of graph convolutional networks on large random graphs
N. Keriven, A. Bietti, and S. Vaiter · 2020
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The Graphon Fourier Transform
L. Ruiz, L. F. O. Chamon, and A. Ribeiro · 2020
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