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Graph Neural Networks (GNNs) have attracted considerable attention and have emerged as a new promising paradigm to process graph-structured data.
Graph convolution for multimodal information extraction from visually rich documents
Xiaojing Liu, Feiyu Gao, Qiong Zhang, and Huasha Zhao · 1903
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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The graph neural network model
F. Scarselli, M. Gori, A. C. Tsoi, M. Hagenbuchner, and G. Monfardini · 2009
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Spectral networks and locally connected networks on graphs
Joan Bruna, Wojciech Zaremba, Arthur Szlam, and Yann LeCun · 2014
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Layer normalization
Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E. Hinton · 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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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling · 2016
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Gated graph sequence neural networks
Yujia Li, Daniel Tarlow, Marc Brockschmidt, and Richard S. Zemel · 2016
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Instance normalization: The missing ingredient for fast stylization
Dmitry Ulyanov, Andrea Vedaldi, and Victor S. Lempitsky · 2016
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Xavier Bresson and Thomas Laurent · 2017
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Inductive representation learning on large graphs
William L. Hamilton, Zhitao Ying, and Jure Leskovec · 2017
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Densely connected convolutional networks
Gao Huang, Zhuang Liu, and Kilian Q. Weinberger · 2017
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Geometric deep learning on graphs and manifolds using mixture model cnns
Federico Monti, Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Jan Svoboda, and Michael M. Bronstein · 2017
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Mastering the game of go without human knowledge
David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, et al · 2017
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Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Fastgcn: fast learning with graph convolutional networks via importance sampling
Jie Chen, Tengfei Ma, and Cao Xiao · 2018
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Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio · 2018
Switchable normalization for learning-to-normalize deep representation
Ping Luo, Ruimao Zhang, Jiamin Ren, Zhanglin Peng, and Jingyu Li · 2019
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Provably powerful graph networks
Haggai Maron, Heli Ben-Hamu, Hadar Serviansky, and Yaron Lipman · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
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Deep graph library: Towards efficient and scalable deep learning on graphs
Minjie Wang, Lingfan Yu, Da Zheng, Quan Gan, Yu Gai, Zihao Ye, Mufei Li, Jinjing Zhou, Qi Huang, Chao Ma, Ziyue Huang, Qipeng Guo, Hao Zhang, Haibin Lin, Junbo Zhao, Jinyang Li, Alexander J Smola, and Zheng Zhang · 2019
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Session-based recommendation with graph neural networks
Shu Wu, Yuyuan Tang, Yanqiao Zhu, Liang Wang, Xing Xie, and Tieniu Tan · 2019
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Zero-shot recognition via semantic embeddings and knowledge graphs
Xiaolong Wang, Yufei Ye, and Abhinav Gupta · 2018
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Group normalization
Yuxin Wu and Kaiming He · 2018
Cited alongside, same era.
Representation learning on graphs with jumping knowledge networks
Keyulu Xu, Chengtao Li, Yonglong Tian, Tomohiro Sonobe, Ken-ichi Kawarabayashi, and Stefanie Jegelka · 2018
Cited alongside, same era.
Graph convolutional networks: Algorithms, applications and open challenges
Si Zhang, Hanghang Tong, Jiejun Xu, and Ross Maciejewski · 2018
Cited alongside, same era.
Pairnorm: Tackling oversmoothing in gnns
Lingxiao Zhao and Leman Akoglu · 2018
Cited alongside, same era.
On the equivalence between graph isomorphism testing and function approximation with gnns
Zhengdao Chen, Soledad Villar, Lei Chen, and Joan Bruna · 2019
Cited alongside, same era.
Graph neural networks for social recommendation
Wenqi Fan, Yao Ma, Qing Li, Yuan He, Eric Zhao, Jiliang Tang, and Dawei Yin · 2019
Cited alongside, same era.
Keyulu Xu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka · 2019
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Graph convolutional networks for text classification
Liang Yao, Chengsheng Mao, and Yuan Luo · 2019
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Skeleton-based action recognition with shift graph convolutional network
Ke Cheng, Yifan Zhang, Xiangyu He, Weihan Chen, Jian Cheng, and Hanqing Lu · 2020
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A new look at ghost normalization
Neofytos Dimitriou and Ognjen Arandjelovic · 2020
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Benchmarking graph neural networks, 2020
Vijay Prakash Dwivedi, Chaitanya K. Joshi, Thomas Laurent, Yoshua Bengio, and Xavier Bresson · 2020
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Spatial pyramid based graph reasoning for semantic segmentation
Xia Li, Yibo Yang, Qijie Zhao, Tiancheng Shen, Zhouchen Lin, and Hong Liu · 2020
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Powernorm: Rethinking batch normalization in transformers, 2020
Sheng Shen, Zhewei Yao, Amir Gholami, Michael W. Mahoney, and Kurt Keutzer · 2020
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Point-gnn: Graph neural network for 3d object detection in a point cloud
Weijing Shi and Raj Rajkumar · 2020
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A comprehensive survey on graph neural networks
Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, and S Yu Philip · 2020
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