Results 21 to 30 of about 1,157 (178)
Residual Enhanced Multi-Hypergraph Neural Network [PDF]
2021 IEEE International Conference on Image Processing (ICIP), 2021 Hypergraphs are a generalized data structure of graphs to model higher-order correlations among entities, which have been successfully adopted into various research domains. Meanwhile, HyperGraph Neural Network (HGNN) is currently the de-facto method for hypergraph representation learning. However, HGNN aims at single hypergraph learning and uses a pre-
Jing Huang, Xiaolin Huang, Jie Yang 0002
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Message Passing Neural Networks for Hypergraphs
, 2022 Hypergraph representations are both more efficient and better suited to describe data characterized by relations between two or more objects. In this work, we present a new graph neural network based on message passing capable of processing hypergraph-structured data.
Sajjad Heydari, Lorenzo Livi
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, 2023 AbstractWith the development of deep learning on high-order correlations, hypergraph neural networks have received much attention in recent years. Generally, the neural networks on hypergraph can be divided into two categories, including the spectral-based methods and the spatial-based methods.
Qionghai Dai, Yue Gao
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Cross-modal Hypergraph Optimisation Learning for Multimodal Sentiment Analysis [PDF]
Jisuanji kexueSentiment expressions are multimodal,and more accurate emotions can be derived through multiple modalities such as verbal,audio,and visual.Studying the interactions among modalities can effectively improve the accuracy of multimodal sentiment analysis ...
JIANG Kun, ZHAO Zhengpeng, PU Yuanyuan, HUANG Jian, GU Jinjing, XU Dan
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Hypergraph Neural Networks for Cross-domain Text-to-SQL [PDF]
Jisuanji gongchengGraph Neural Network (GNN) have been widely used as encoders in recent years for cross-domain Text-to-SQL. The encoding process based on GNN substantially improves the generalization of generative models under cross-domain Text-to-SQL by capturing the ...
HAO Zhifeng, LI Yanglin, XU Boyan, CAI Ruichu
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Deep Learning-Based Community Detection Approach on Multimedia Social Networks
Applied Sciences, 2021 Exploiting multimedia data to analyze social networks has recently become one the most challenging issues for Social Network Analysis (SNA), leading to defining Multimedia Social Networks (MSNs).
Antonino Ferraro +2 more
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Text Classification Based on Feature Fusion of Dual Hypergraph Neural Networks [PDF]
Jisuanji gongchengIn recent years, Graph Neural Networks (GNNs) have been widely used for text classification tasks. Current models based on GNNs first model the text as a graph and then use GNNs to propagate and aggregate the features of the text graph.
ZHENG Cheng, LI Pengfei
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Investigating Hypernode Classification of Complex Systems Based on High-order Graph Neural Networks
Guidance, Navigation and ControlInvestigating latent interactions beyond direct connections is essential for analyzing complex networks. However, traditional graph structures often fail to capture complex relationships, especially in the high-order interactions among multiple ...
Jiawen Chen +3 more
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Hierarchical Hypergraph-based Attention Neural Network for Service Recommendation [PDF]
Jisuanji kexueWith the rapid growth of various services and APIs on the Internet and the Web,it has become increasingly challenging for developers to quickly and accurately find APIs that meet their needs,thus requiring an efficient recommendation system.Currently,the
YANG Dongsheng, WANG Guiling, ZHENG Xin
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Hypergraph Pre-training with Graph Neural Networks
CoRR, 2021 Despite the prevalence of hypergraphs in a variety of high-impact applications, there are relatively few works on hypergraph representation learning, most of which primarily focus on hyperlink prediction, often restricted to the transductive learning setting.
Boxin Du +4 more
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