Results 1 to 10 of about 5,998 (189)

Hyperbolic multi-channel hypergraph convolutional neural network based on multilayer hypergraph [PDF]

Scientific Reports
In 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, Feng Hu, Chunyang Tang, Zhangyu Mei, Chuang Liu   +4 more
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A lightweight single-view contrastive learning hypergraph neural network for food–microbe–disease association prediction [PDF]

BMC Bioinformatics
Background Identifying potential associations among food, gut microbiota and disease is fundamental for elucidating interaction mechanisms and advancing personalized healthy dietary strategies. While computational methods have been extensively applied to
Jianqiang Hu, Mingyi Hu, Yangxiang Wu, Songyao Mu, Dahao Huang, Baolong Wang, Yuchen Gao, Shixin Gu, Jinlin Zhu   +8 more
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Hierarchical Network Organization and Dynamic Perturbation Propagation in Autism Spectrum Disorder: An Integrative Machine Learning and Hypergraph Analysis Reveals Super-Hub Genes and Therapeutic Targets [PDF]

Biomedicines
Background/Objectives: Autism spectrum disorder (ASD) exhibits remarkable genetic heterogeneity involving hundreds of risk genes; however, the mechanism by which these genes organize within biological networks to contribute to disease pathogenesis ...
Larissa Margareta Batrancea, Ömer Akgüller, Mehmet Ali Balcı, Lucian Gaban   +3 more
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HyperGraph-based capsule temporal memory network for efficient and explainable diabetic retinopathy detection in retinal imaging [PDF]

Scientific Reports
Diabetic retinopathy (DR) is a chronic complication of diabetes in which the retinal damage may cause vision impairment or blindness if left untreated. The challenges in DR detection are mostly due to the morphological variations of retinal lesions, e.g.,
Mishmala Sushith, N. Malligeswari, M. Anlin Sahaya Infant Tinu, M. Jaiganesh   +3 more
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Adaptive dynamic hypergraph learning for ingredient aware food recommendation [PDF]

Scientific Reports
Food recommendation systems face fundamental challenges in modeling the complex, compositional relationships among users, foods, and ingredients. Traditional collaborative filtering and Graph Neural Networks rely on pairwise connections that oversimplify
Yazeed Alkhrijah, Abbas N. Talib, Narinderjit Singh Sawaran Singh, Ashraf Abed Hussein   +3 more
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Hypergraph-based contrastive learning for enhanced fraud detection [PDF]

Frontiers in Artificial Intelligence
The proliferation of digital platforms has enabled fraudsters to deploy sophisticated camouflage techniques, such as multi-hop collaborative attacks, to evade detection.
Qinhong Wang, Yiming Shen, Husheng Dong
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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
doaj   +1 more source

Model of the malicious traffic classification based on hypergraph neural network

网络与信息安全学报, 2023
As the use and reliance on networks continue to grow, the prevalence of malicious network traffic poses a significant challenge in the field of network security.Cyber attackers constantly seek new ways to infiltrate systems, steal data, and disrupt ...
Wenbo ZHAO, Zitong MA, Zhe YANG
doaj   +3 more sources

Signal Contrastive Enhanced Graph Collaborative Filtering for Recommendation

Data Science and Engineering, 2023
Graph collaborative filtering methods have shown great performance improvements compared with deep neural network-based models. However, these methods suffer from data sparsity and data noise problems.
Zhi-Yuan Li, Man-Sheng Chen, Yuefang Gao, Chang-Dong Wang   +3 more
doaj   +1 more source

Android Malware Detection Based on Hypergraph Neural Networks

Applied Sciences, 2023
Android has been the most widely used operating system for mobile phones over the past few years. Malicious attacks against android are a major privacy and security concern. Malware detection techniques for android applications are therefore significant.
Dehua Zhang, Xiangbo Wu, Erlu He, Xiaobo Guo, Xiaopeng Yang, Ruibo Li, Hao Li   +6 more
doaj   +1 more source