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Hypergraphs provide a natural representation for many real world datasets.
Indexing by latent semantic analysis
S. Deerwester, S. T. Dumais, G. W. Furnas, T. K. Landauer, and R Harshman · 1990
Earlier work this paper cites.
Multilevel spectral hypergraph partitioning with arbitrary vertex sizes
Jason Y Zien, Martine DF Schlag, and Pak K Chan · 1999
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Link-based classification
Qing Liu and Lise Getoor · 2003
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Higher order learning with graphs
Sameer Agarwal, Kristin Branson, and Serge Belongie · 2006
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Collective entity resolution in relational data
Indrajit Bhattacharya and Lise Getoor · 2007
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Learning with hypergraphs: clustering, classification, and embedding
Denny Zhou, Jiayuan Huang, and Bernhard Schölkopf · 2007
Earlier work this paper cites.
On the first eigenvalue of bipartite graphs
Amitava Bhattacharya, Shmuel Friedland, and Uri N Peled · 2008
Earlier work this paper cites.
Hypergraph spectral learning for multi-label classification
Liang Sun, Shuiwang Ji, and Jieping Ye · 2008
Earlier work this paper cites.
Collective classification in network data
P Sen, G Namata, M Bilgic, L Getoor, B Galligher, and T Eliassi-Rad · 2008
Cited alongside, same era.
Deep sparse rectifier neural networks
Xavier Glorot, Antoine Bordes, and Yoshua Bengio · 2011
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Query-driven active surveying for collective classification
Galileo Namata, Ben London, Lise Getoor, and Bert Huang · 2012
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Dropout: A simple way to prevent neural networks from overfitting
N Srivastava, G Hinton, A Krizhevsky, I Sutskever, and R Salakhutdinov · 2014
Cited alongside, same era.
Adam: A method for stochastic optimization
Diederik Kingma and Jimmy Ba · 2015
Cited alongside, same era.
Molecular graph convolutions: moving beyond fingerprints
Steven Kearnes, Kevin McCloskey, Marc Berndl, Vijay Pande, and Patrick Riley · 2016
Cited alongside, same era.
Hypergraph neural networks
Yifan Feng, Haoxuan You, Zizhao Zhang, Rongrong Ji, and Yue Gao · 2018
Later among the works it cites.
Beyond link prediction: Predicting hyperlinks in adjacency space
Shali Jiang Muhan Zhang, Zhicheng Cui and Yixin Chen · 2018
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Structural deep embedding for hypernetworks
Ke Tu, Peng Cui, Xiao Wang, Fei Wang, and Wenwu Zhu · 2018
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Graph processing on GPUs: where are the bottlenecks?
Qiumin Xu, Hyeran Jeon, and Murali Annavaram · 2018
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Hypergraph convolution and hypergraph attention
Song Bai, Feihu Zhang, and Philip H.S. Torr · 2019
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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
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Neural message passing for quantum chemistry
Justin Gilmer, Samuel S. Schoenholz, Patrick F. Riley, Oriol Vinyals, and George E. Dahl · 2017
Cited alongside, same era.
Semi-supervised classification with graph convolutional networks
Thomas Kipf and Max Welling · 2017
Cited alongside, same era.
AMiner DBLP data
AMiner
Cited in the paper.
Citeseer for document classification
UCSC Statistical Relational Learning Group
Cited in the paper.
Cora information extraction data
Andrew Mccallum
Cited in the paper.
Later among the works it cites.
Hyper-SAGNN: a self-attention based graph neural network for hypergraphs
Ruochi Zhang, Yuesong Zou, and Jian Ma · 2019
Later among the works it cites.
Generalizing the hypergraph Laplacian via a diffusion process with mediators
T. H. Hubert Chan and Zhibin Liang · 2020
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