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Graph neural networks (GNNs) are widely used in the applications based on graph structured data, such as node classification and link prediction.
Multi-scale attributed node embedding
Rozemberczki, B.; Allen, C.; and Sarkar, R. 2019 · 1909
Earlier work this paper cites.
Non-Local Graph Neural Networks
Liu, M.; Wang, Z.; and Ji, S. 2020 · 2005
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Joint adaptive feature smoothing and topology extraction via generalized pagerank gnns
Chien, E.; Peng, J.; Li, P.; and Milenkovic, O. 2020 · 2006
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Generalizing graph neural networks beyond homophily
Zhu, J.; Yan, Y.; Zhao, L.; Heimann, M.; Akoglu, L.; and Koutra, D. 2020 · 2006
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The graph neural network model
Scarselli, F.; Gori, M.; Tsoi, A. C.; Hagenbuchner, M.; and Monfardini, G. 2008 · 2008
Earlier work this paper cites.
Collective classification in network data
Sen, P.; Namata, G.; Bilgic, M.; Getoor, L.; Galligher, B.; and Eliassi-Rad, T. 2008 · 2008
Earlier work this paper cites.
Distance Encoding–Design Provably More Powerful GNNs for Structural Representation Learning
Li, P.; Wang, Y.; Wang, H.; and Leskovec, J. 2020 · 2009
Earlier work this paper cites.
Social influence analysis in large-scale networks
Tang, J.; Sun, J.; Wang, C.; and Yang, Z. 2009 · 2009
Earlier work this paper cites.
Combining Label Propagation and Simple Models Out-performs Graph Neural Networks
Huang, Q.; He, H.; Singh, A.; Lim, S.-N.; and Benson, A. R. 2020 · 2010
Earlier work this paper cites.
Rolx: structural role extraction & mining in large graphs
Henderson, K.; Gallagher, B.; Eliassi-Rad, T.; Tong, H.; Basu, S.; Akoglu, L.; Koutra, D.; Faloutsos, C.; and Li, L. 2012 · 2012
Cited alongside, same era.
Query-driven active surveying for collective classification
Namata, G.; London, B.; Getoor, L.; Huang, B.; and EDU, U. 2012 · 2012
Cited alongside, same era.
Adam: A Method for Stochastic Optimization
Kingma, D. P.; and Ba, J. 2015 · 2015
Cited alongside, same era.
node2vec: Scalable feature learning for networks
Grover, A.; and Leskovec, J. 2016 · 2016
Cited alongside, same era.
Variational graph auto-encoders
Kipf, T. N.; and Welling, M. 2016 · 2016
Cited alongside, same era.
Semi-Supervised Classification with Graph Convolutional Networks
Kipf, T. N.; and Welling, M. 2017 · 2017
Cited alongside, same era.
Link prediction based on graph neural networks
Zhang, M.; and Chen, Y. 2018 · 2018
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Predict then propagate: Graph neural networks meet personalized pagerank
Klicpera, J.; Bojchevski, A.; and Günnemann, S. 2019 · 2019
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Diffusion Improves Graph Learning
Klicpera, J.; Weißenberger, S.; and Günnemann, S. 2019 · 2019
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Optimizing Generalized PageRank Methods for Seed-Expansion Community Detection
Li, P.; Chien, I.; and Milenkovic, O. 2019 · 2019
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Simplifying Graph Convolutional Networks
Wu, F.; Souza, A.; Zhang, T.; Fifty, C.; Yu, T.; and Weinberger, K. 2019 · 2019
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Role-based Graph Embeddings
Ahmed, N.; Rossi, R. A.; Lee, J.; Willke, T.; Zhou, R.; Kong, X.; and Eldardiry, H. 2020 · 2020
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struc2vec: Learning node representations from structural identity
Ribeiro, L. F.; Saverese, P. H.; and Figueiredo, D. R. 2017 · 2017
Cited alongside, same era.
Relational inductive biases, deep learning, and graph networks
Battaglia, P. W.; Hamrick, J. B.; Bapst, V.; Sanchez-Gonzalez, A.; Zambaldi, V.; Malinowski, M.; Tacchetti, A.; Raposo, D.; Santoro, A.; Faulkner, R.; et al. 2018 · 2018
Cited alongside, same era.
Graph attention networks
Veličković, P.; Cucurull, G.; Casanova, A.; Romero, A.; Lio, P.; and Bengio, Y. 2018 · 2018
Cited alongside, same era.
Inductive representation learning on large graphs
Hamilton, W.; Ying, Z.; and Leskovec, J. 2017a
Cited in the paper.
Representation learning on graphs: Methods and applications
Hamilton, W. L.; Ying, R.; and Leskovec, J. 2017b
Cited in the paper.
Geom-gcn: Geometric graph convolutional networks
Pei, H.; Wei, B.; Chang, K. C.-C.; Lei, Y.; and Yang, B. 2020 · 2020
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On the Equivalence between Node Embeddings and Structural Graph Representations
Srinivasan, B.; and Ribeiro, B. 2020 · 2020
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