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In this work, we introduce a hypergraph representation learning framework called Hypergraph Neural Networks (HNN) that jointly learns hyperedge embeddings along with a set of hyperedge-dependent embeddings for each node in the hypergraph.
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Hypergraph Convolution and Hypergraph Attention
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Knowledge Hypergraphs: Prediction Beyond Binary Relations
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Heterogeneous Hypergraph Variational Autoencoder for Link Prediction
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Hierarchical Hyperedge Embedding-based Representation Learning for Group Recommendation
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Hypergraph Neural Network for Skeleton-Based Action Recognition
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Hypergraph Convolutional Network for Group Recommendation. In 2021 IEEE International Conference on Data Mining (ICDM) . IEEE, 260–269
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Hypergraph Induced Convolutional Manifold Networks. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (Macao, China) (IJCAI’19) . AAAI Press, 2670–2676
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Attention models in graphs: A survey
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KGAT. In KDD . ACM
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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 · 2019
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Personalized recommendation based on hierarchical interest overlapping community
Jianxing Zheng, Suge Wang, Deyu Li, and Bofeng Zhang. 2019 · 2019
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Hypersage: Generalizing inductive representation learning on hypergraphs
Devanshu Arya, Deepak K Gupta, Stevan Rudinac, and Marcel Worring. 2020 · 2020
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Neural feature-aware recommendation with signed hypergraph convolutional network
Xu Chen, Kun Xiong, Yongfeng Zhang, Long Xia, Dawei Yin, and Jimmy Xiangji Huang. 2020 · 2020
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Heterogeneous Hypergraph Embedding for Graph Classification. In Proceedings of the 14th ACM International Conference on Web Search and Data Mining (Virtual Event, Israel) (WSDM ’21) . 725–733
Xiangguo Sun, Hongzhi Yin, Bo Liu, Hongxu Chen, Jiuxin Cao, Yingxia Shao, and Nguyen Quoc Viet Hung. 2021 · 2021
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A nonlinear diffusion method for semi-supervised learning on hypergraphs
Francesco Tudisco, Konstantin Prokopchik, and Austin R Benson. 2021 · 2021
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Principled Hyperedge Prediction with Structural Spectral Features and Neural Networks
Changlin Wan, Muhan Zhang, Wei Hao, Sha Cao, Pan Li, and Chi Zhang. 2021 · 2021
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Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation
Xin Xia, Hongzhi Yin, Junliang Yu, Qinyong Wang, Lizhen Cui, and Xiangliang Zhang. 2021 · 2021
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Multiplex bipartite network embedding using dual hypergraph convolutional networks. In Proceedings of the Web Conference 2021 . 1649–1660
Hansheng Xue, Luwei Yang, Vaibhav Rajan, Wen Jiang, Yi Wei, and Yu Lin. 2021 · 2021
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Inhomogeneous Social Recommendation with Hypergraph Convolutional Networks
Zirui Zhu, Chen Gao, Xu Chen, Nian Li, Depeng Jin, and Yong Li. 2021 · 2021
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Generating Hypergraph-Based High-Order Representations of Whole-Slide Histopathological Images for Survival Prediction
Donglin Di, Changqing Zou, Yifan Feng, Haiyan Zhou, Rongrong Ji, Qionghai Dai, and Yue Gao. 2022 · 2022
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HEAT: Hyperedge Attention Networks
Dobrik Georgiev, Marc Brockschmidt, and Miltiadis Allamanis. 2022 · 2022
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Equivariant Hypergraph Neural Networks
Jinwoo Kim, Saeyoon Oh, Sungjun Cho, and Seunghoon Hong. 2022 · 2022
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Music Recommendation via Hypergraph Embedding
Valerio La Gatta, Vincenzo Moscato, Mirko Pennone, Marco Postiglione, and Giancarlo Sperlí. 2022 · 2022
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VisGNN: Personalized Visualization Recommendation via Graph Neural Networks. In Proceedings of the ACM Web Conference . 2810–2818
Fayokemi Ojo, Ryan A Rossi, Jane Hoffswell, Shunan Guo, Fan Du, Sungchul Kim, Chang Xiao, and Eunyee Koh. 2022 · 2022
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Motifs-based Recommender System via Hypergraph Convolution and Contrastive Learning
Yundong Sun, Dongjie Zhu, Haiwen Du, and Zhaoshuo Tian. 2022 · 2022
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Graph Neural Networks Designed for Different Graph Types: A Survey
Josephine M Thomas, Alice Moallemy-Oureh, Silvia Beddar-Wiesing, and Clara Holzhüter. 2022 · 2022
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Joint Personalized Search and Recommendation with Hypergraph Convolutional Networks. In European Conference on Information Retrieval . Springer, 443–456
Thibaut Thonet, Jean-Michel Renders, Mario Choi, and Jinho Kim. 2022 · 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 · 2022
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Hypergraph contrastive collaborative filtering. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval . 70–79
Lianghao Xia, Chao Huang, Yong Xu, Jiashu Zhao, Dawei Yin, and Jimmy Huang. 2022 · 2022
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LBSN2Vec++: Heterogeneous Hypergraph Embedding for Location-Based Social Networks
Dingqi Yang, Bingqing Qu, Jie Yang, and Philippe Cudré-Mauroux. 2022 · 2022
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Hypergraph Convolutional Networks via Equivalency between Hypergraphs and Undirected Graphs
Jiying Zhang, Fuyang Li, Xi Xiao, Tingyang Xu, Yu Rong, Junzhou Huang, and Yatao Bian. 2022c · 2022
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Deep Hypergraph Structure Learning
Zizhao Zhang, Yifan Feng, Shihui Ying, and Yue Gao. 2022b · 2022
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DDHH: A decentralized deep learning framework for large-scale heterogeneous networks. In 2021 IEEE 37th International Conference on Data Engineering (ICDE) . IEEE, 2033–2038
Mubashir Imran, Hongzhi Yin, Tong Chen, Zi Huang, Xiangliang Zhang, and Kai Zheng. 2021 · 2038
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