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Graph convolutional networks (GCNs) have recently received wide attentions, due to their successful applications in different graph tasks and different domains.
Convolutional networks for images, speech, and time series
Yann LeCun, Yoshua Bengio, et al · 1995
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Bagging predictors
Leo Breiman · 1996
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Collective classification in network data
Prithviraj Sen, Galileo Namata, Mustafa Bilgic, Lise Getoor, Brian Galligher, and Tina Eliassi-Rad · 2008
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Discriminative embeddings of latent variable models for structured data
Hanjun Dai, Bo Dai, and Le Song · 2016
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Convolutional neural networks on graphs with fast localized spectral filtering
Michaël Defferrard, Xavier Bresson, and Pierre Vandergheynst · 2016
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Train faster, generalize better: Stability of stochastic gradient descent
Moritz Hardt, Ben Recht, and Yoram Singer · 2016
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Geometric deep learning: going beyond euclidean data
Michael M Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, and Pierre Vandergheynst · 2017
Cited alongside, same era.
Representation learning on graphs: Methods and applications
William L. Hamilton, Rex Ying, and Jure Leskovec · 2017
Cited alongside, same era.
Inductive representation learning on large graphs
William L. Hamilton, Zhitao Ying, and Jure Leskovec · 2017
Cited alongside, same era.
Layered adaptive importance sampling
Luca Martino, Victor Elvira, David Luengo, and Jukka Corander · 2017
Cited alongside, same era.
Stochastic training of graph convolutional networks with variance reduction
Jianfei Chen, Jun Zhu, and Le Song · 2018
Cited alongside, same era.
Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling
Cited in the paper.
Fastgcn: Fast learning with graph convolutional networks via importance sampling
Jie Chen, Tengfei Ma, and Cao Xiao · 2018
Later among the works it cites.
Adaptive sampling towards fast graph representation learning
Wen-bing Huang, Tong Zhang, Yu Rong, and Junzhou Huang · 2018
Later among the works it cites.
Modeling relational data with graph convolutional networks
Michael Sejr Schlichtkrull, Thomas N. Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, and Max Welling · 2018
Later among the works it cites.
Graph convolutional neural networks for web-scale recommender systems
Rex Ying, Ruining He, Kaifeng Chen, Pong Eksombatchai, William L. Hamilton, and Jure Leskovec · 2018
Later among the works it cites.
Cluster-gcn: An efficient algorithm for training deep and large graph convolutional networks
Wei-Lin Chiang, Xuanqing Liu, Si Si, Yang Li, Samy Bengio, and Cho-Jui Hsieh · 2019
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