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Higher-order relations are widespread in nature, with numerous phenomena involving complex interactions that extend beyond simple pairwise connections.
Order and flexibility in the motion of fish schools
Yoshinobu Inada and Keiji Kawachi · 2002
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Higher order learning with graphs
Sameer Agarwal, Kristin Branson, and Serge Belongie · 2006
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Legislative cosponsorship networks in the US house and senate
James H. Fowler · 2006
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Spectral networks and locally connected networks on graphs
Joan Bruna, Wojciech Zaremba, Arthur Szlam, and Yann LeCun · 2013
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The total variation on hypergraphs - learning on hypergraphs revisited
Matthias Hein, Simon Setzer, Leonardo Jost, and Syama Sundar Rangapuram · 2013
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The hubs of the human connectome are generally implicated in the anatomy of brain disorders
Nicolas A. Crossley, Andrea Mechelli, Jessica Scott, Francesco Carletti, Peter T. Fox, Philip K. McGuire, and Edward T. Bullmore · 2014
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Sheaves, cosheaves and applications, 2014
Justin Curry · 2014
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Consistency of spectral partitioning of uniform hypergraphs under planted partition model
Debarghya Ghoshdastidar and Ambedkar Dukkipati · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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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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Identifying high order brain connectome biomarkers via learning on hypergraph
Chen Zu, Yue Gao, Brent Munsell, Minjeong Kim, Ziwen Peng, Yingying Zhu, Wei Gao, Daoqiang Zhang, Dinggang Shen, and Guorong Wu · 2016
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Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling · 2017
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Modeling relational data with graph convolutional networks, 2017
Michael Schlichtkrull, Thomas N. Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, and Max Welling · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin · 2017
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Deep sets
Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabas Poczos, Russ R Salakhutdinov, and Alexander J Smola · 2017
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Re-revisiting learning on hypergraphs: Confidence interval and subgradient method
Chenzi Zhang, Shuguang Hu, Zhihao Gavin Tang, and T-H. Hubert Chan · 2017
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Graph convolutional neural networks for web-scale recommender systems
Rex Ying, Ruining He, Kaifeng Chen, Pong Eksombatchai, William L Hamilton, and Jure Leskovec · 2018
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Videos as space-time region graphs
Xiaolong Wang and Abhinav Gupta · 2018
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Hypergraph laplace operators for chemical reaction networks, 2018
Jürgen Jost and Raffaella Mulas · 2018
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Spectral properties of hypergraph laplacian and approximation algorithms
T.-H. Hubert Chan, Anand Louis, Zhihao Gavin Tang, and Chenzi Zhang · 2018
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Spatio-temporal graph convolutional networks: A deep learning framework for traffic forecasting
Bing Yu, Haoteng Yin, and Zhanxing Zhu · 2018
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Hypergraph p-laplacian: A differential geometry view
Shota Saito, Danilo Mandic, and Hideyuki Suzuki · 2018
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Contextual stochastic block models
Yash Deshpande, Subhabrata Sen, Andrea Montanari, and Elchanan Mossel · 2018
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Community detection in hypergraphs: Optimal statistical limit and efficient algorithms
I Chien, Chung-Yi Lin, and I-Hsiang Wang · 2018
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Generalizing the Hypergraph Laplacian via a Diffusion Process with Mediators
T.-H Chan and Zhibin Liang · 2018
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Hypergraph neural networks
Yifan Feng, Haoxuan You, Zizhao Zhang, Rongrong Ji, and Yue Gao · 2019
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Fake news detection on social media using geometric deep learning
Federico Monti, Fabrizio Frasca, Davide Eynard, Damon Mannion, and Michael M Bronstein · 2019
Opinion dynamics on discourse sheaves
Jakob Hansen and Robert Ghrist · 2021
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Unignn: a unified framework for graph and hypergraph neural networks
Jing Huang and Jie Yang · 2021
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Nonlinear higher-order label spreading
Francesco Tudisco, Austin R. Benson, and Konstantin Prokopchik · 2021
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Predicting Patient Outcomes with Graph Representation Learning
Catherine Tong, Emma Rocheteau, Petar Veličković, Nicholas Lane, and Pietro Lio · 2022
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Hypergraph factorisation for multi-tissue gene expression imputation
Ramon Viñas, Chaitanya K. Joshi, Dobrik Georgiev, Bianca Dumitrascu, Eric R. Gamazon, and Pietro Liò · 2022
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An evolving hypergraph convolutional network for the diagnosis of alzheimers disease
Xinlei Wang, Junchang Xin, Zhongyang Wang, Chuangang Li, and Zhiqiong Wang · 2022
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Toward a spectral theory of cellular sheaves
Jakob Hansen and Robert Ghrist · 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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Hypergraph convolution and hypergraph attention
Song Bai, Feihu Zhang, and Philip H. S. Torr · 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, Alban Desmaison, Andreas Köpf, Edward Z. Yang, Zach DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
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Skipgnn: predicting molecular interactions with skip-graph networks
Kexin Huang, Cao Xiao, Lucas M Glass, Marinka Zitnik, and Jimeng Sun · 2020
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Learning multi-granular hypergraphs for video-based person re-identification
Yichao Yan, Jie Qin, Jiaxin Chen, Li Liu, Fan Zhu, Ying Tai, and Ling Shao · 2020
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HEAT: Hyperedge attention networks
Dobrik Georgiev Georgiev, Marc Brockschmidt, and Miltiadis Allamanis · 2022
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Multitask hypergraph convolutional networks: A heterogeneous traffic prediction framework
Jingcheng Wang, Yong Zhang, Lixun Wang, Yongli Hu, Xinglin Piao, and Baocai Yin · 2022
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Preventing over-smoothing for hypergraph neural networks
Guanzi Chen, Jiying Zhang, Xi Xiao, and Yang Li · 2022
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Neural sheaf diffusion: A topological perspective on heterophily and oversmoothing in GNNs
Cristian Bodnar, Francesco Di Giovanni, Benjamin Paul Chamberlain, Pietro Liò, and Michael M. Bronstein · 2022
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Sheaf neural networks with connection laplacians
Federico Barbero, Cristian Bodnar, Haitz Sáez de Ocáriz Borde, Michael Bronstein, Petar Veličković, and Pietro Lio · 2022
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Sheaf attention networks
Federico Barbero, Cristian Bodnar, Haitz Sáez de Ocáriz Borde, and Pietro Lio · 2022
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Surfing on the neural sheaf
Julian Suk, Lorenzo Giusti, Tamir Hemo, Miguel Lopez, Konstantinos Barmpas, and Cristian Bodnar · 2022
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Sspro/accpro 6: almost perfect prediction of protein secondary structure and relative solvent accessibility using profiles, deep learning and structural similarity
Gregor Urban, Christophe N. Magnan, and Pierre Baldi · 2022
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Learnable hypergraph laplacian for hypergraph learning
Jiying Zhang, Yuzhao Chen, Xiong Xiao, Runiu Lu, and Shutao Xia · 2022
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You are allset: A multiset function framework for hypergraph neural networks
Eli Chien, Chao Pan, Jianhao Peng, and Olgica Milenkovic · 2022
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Equivariant hypergraph diffusion neural operators
Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, and Pan Li · 2022
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High-order pooling for graph neural networks with tensor decomposition, 2022
Chenqing Hua, Guillaume Rabusseau, and Jian Tang · 2022
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Sheaf neural networks for graph-based recommender systems, 2023
Antonio Purificato, Giulia Cassarà, Pietro Liò, and Fabrizio Silvestri · 2023
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A non-asymptotic analysis of oversmoothing in graph neural networks
Xinyi Wu, Zhengdao Chen, William Wei Wang, and Ali Jadbabaie · 2023
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Normalized laplacian eigenvalues of hypergraphs, 2023
Leyou Xu and Bo Zhou · 2023
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