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Hyperbolic multi-channel hypergraph convolutional neural network based on multilayer hypergraph [PDF]
Scientific ReportsIn recent years, hypergraph neural networks have achieved remarkable success in tasks such as node classification, link prediction, and graph classification, thanks to their powerful computational capabilities.
Libing Bai +4 more
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Dual-branch differential channel hypergraph convolutional network for human skeleton based action recognition. [PDF]
PLoS ONEGraph Convolutional Networks (GCNs) perform well in skeleton action recognition tasks, but their pairwise node connections make it difficult to effectively model high-order dependencies between non-adjacent joints.
Dong Chen +4 more
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On edge product hypergraphs [PDF]
Journal of Hyperstructures, 2021 In this paper we introduced the notion of an edge product hypergraph. A hypergraph H is said to be an edge producthypergraph if edges of hypergraph can be labeled with distinct positive integers such that the product of all the labels of edges incident ...
Kishor F. Pawar, Megha M. Jadhav
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Multimodal Data Fusion Algorithm Based on Hypergraph Regularization [PDF]
Jisuanji kexue, 2023 The multi-modal data fusion improves the performance of data classification and prediction by learning the correlation information and complementary information between multiple datasets.However,existing data fusion methods are based on feature pattern ...
CUI Bingjing, ZHANG Yipu, WANG Biao
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On domination in an edge product hypergraphs [PDF]
Journal of Hyperstructures, 2021 In this paper, we study domination in an edge product hypergraphs and found some results on it. It is proved that theunit edge in a unit edge product hypergraph is a dominating set of hypergraph H.
Kishor F. Pawar, Megha M. Jadhav
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Unified Low-Rank Subspace Clustering with Dynamic Hypergraph for Hyperspectral Image
Remote Sensing, 2021 Low-rank representation with hypergraph regularization has achieved great success in hyperspectral imagery, which can explore global structure, and further incorporate local information.
Jinhuan Xu, Liang Xiao, Jingxiang Yang
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The treewidth of 2-section of hypergraphs [PDF]
Discrete Mathematics & Theoretical Computer Science, 2021 Let $H=(V,F)$ be a simple hypergraph without loops. $H$ is called linear if $|f\cap g|\le 1$ for any $f,g\in F$ with $f\not=g$. The $2$-section of $H$, denoted by $[H]_2$, is a graph with $V([H]_2)=V$ and for any $ u,v\in V([H]_2)$, $uv\in E([H]_2)$ if ...
Ke Liu, Mei Lu
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Multi-site Hyper-graph Convolutional Neural Networks and Application [PDF]
Jisuanji kexue, 2022 Recently,the exploitation of graph neural networks for neurological brain disorder diagnosis has attracted much attention.However,the graphs used in the existing studies are usually based on the pairwise connections of different nodes,and thus cannot ...
ZHOU Hai-yu, ZHANG Dao-qiang
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The k-annihilating-ideal hypergraph of commutative ring
AKCE International Journal of Graphs and Combinatorics, 2019 The concept of the annihilating-ideal graph of a commutative ring was introduced by Behboodi et. al in 2011. In this paper, we extend this concept to the hypergraph for which we define an algebraic structure called k-annihilating-ideal of a commutative ...
K. Selvakumar, V. Ramanathan
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Multi-order hypergraph convolutional networks integrated with self-supervised learning
Complex & Intelligent Systems, 2023 Hypergraphs, as a powerful representation of information, effectively and naturally depict complex and non-pair-wise relationships in the real world. Hypergraph representation learning is useful for exploring complex relationships implicit in hypergraphs.
Jiahao Huang +5 more
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