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In recent years, hypergraph learning has attracted great attention due to its capacity in representing complex and high-order relationships.
Learning with hypergraphs: Clustering, classification, and embedding
Dengyong Zhou, Jiayuan Huang, and Bernhard Schölkopf · 2007
Earlier work this paper cites.
Hypergraph spectral learning for multi-label classification
Liang Sun, Shuiwang Ji, and Jieping Ye · 2008
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Image retrieval via probabilistic hypergraph ranking
Yuchi Huang, Qingshan Liu, Shaoting Zhang, and Dimitris N Metaxas · 2010
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Higher-order correlation clustering for image segmentation
Sungwoong Kim, Sebastian Nowozin, Pushmeet Kohli, and Chang Yoo · 2011
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Adaptive hypergraph learning and its application in image classification
Jun Yu, Dacheng Tao, and Meng Wang · 2012
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Mapping users across networks by manifold alignment on hypergraph
Shulong Tan, Ziyu Guan, Deng Cai, Xuzhen Qin, Jiajun Bu, and Chun Chen · 2014
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling · 2017
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Deeper insights into graph convolutional networks for semi-supervised learning
Qimai Li, Zhichao Han, and Xiao-Ming Wu · 2018
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Representation learning on graphs with jumping knowledge networks
Keyulu Xu, Chengtao Li, Yonglong Tian, Tomohiro Sonobe, Ken-ichi Kawarabayashi, and Stefanie Jegelka · 2018
Earlier work this paper cites.
Hypergraph convolution and hypergraph attention
Song Bai, Feihu Zhang, and Philip HS Torr · 2019
Cited alongside, same era.
Hypergraph neural networks
Yifan Feng, Haoxuan You, Zizhao Zhang, Rongrong Ji, and Yue Gao · 2019
Cited alongside, same era.
Combining neural networks with personalized pagerank for classification on graphs
Johannes Klicpera, Aleksandar Bojchevski, and Stephan Günnemann · 2019
Cited alongside, same era.
Dropedge: Towards deep graph convolutional networks on node classification
Yu Rong, Wenbing Huang, Tingyang Xu, and Junzhou Huang · 2019
Cited alongside, same era.
Simplifying graph convolutional networks
Felix Wu, Tianyi Zhang, Amauri Holanda de Souza Jr, Christopher Fifty, Tao Yu, and Kilian Q Weinberger · 2019
Cited alongside, same era.
Hypergraph learning: Methods and practices
Yue Gao, Zizhao Zhang, Haojie Lin, Xibin Zhao, Shaoyi Du, and Changqing Zou · 2020
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Scattering gcn: Overcoming oversmoothness in graph convolutional networks
Yimeng Min, Frederik Wenkel, and Guy Wolf · 2020
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Pairnorm: Tackling oversmoothing in {gnn}s
Lingxiao Zhao and Leman Akoglu · 2020
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Towards deeper graph neural networks with differentiable group normalization
Kaixiong Zhou, Xiao Huang, Yuening Li, Daochen Zha, Rui Chen, and Xia Hu · 2020
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Diversified multiscale graph learning with graph self-correction
Yuzhao Chen, Yatao Bian, Jiying Zhang, Xi Xiao, Tingyang Xu, Yu Rong, and Junzhou Huang · 2021
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Hypergcn: A new method for training graph convolutional networks on hypergraphs
Naganand Yadati, Madhav Nimishakavi, Prateek Yadav, Vikram Nitin, Anand Louis, and Partha Talukdar · 2019
Cited alongside, same era.
A note on over-smoothing for graph neural networks
Chen Cai and Yusu Wang · 2020
Cited alongside, same era.
Simple and deep graph convolutional networks
Ming Chen, Zhewei Wei, Zengfeng Huang, Bolin Ding, and Yaliang Li · 2020
Cited alongside, same era.
Be more with less: Hypergraph attention networks for inductive text classification
Kaize Ding, Jianling Wang, Jundong Li, Dingcheng Li, and Huan Liu · 2020
Cited alongside, same era.
Hnhn: Hypergraph networks with hyperedge neurons
Yihe Dong, Will Sawin, and Yoshua Bengio · 2020
Cited alongside, same era.
Guanzi Chen, Jiying Zhang, Xi Xiao, and Yang Li · 2022
Closest in time.
A simple hypergraph kernel convolution based on discounted markov diffusion process
Fuyang Li, Jiying Zhang, Xi Xiao, bin zhang, and Dijun Luo · 2022
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Learnable hypergraph laplacian for hypergraph learning
Jiying Zhang, Yuzhao Chen, Xi Xiao, Runiu Lu, and Shu-Tao Xia · 2022
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Hypergraph convolutional networks via equivalency between hypergraphs and undirected graphs, 2022
Jiying Zhang, Fuyang Li, Xi Xiao, Tingyang Xu, Yu Rong, Junzhou Huang, and Yatao Bian · 2022
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Fine-tuning graph neural networks via graph topology induced optimal transport
Jiying Zhang, Xi Xiao, Long-Kai Huang, Yu Rong, and Yatao Bian · 2022
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