Results 21 to 30 of about 5,998 (189)
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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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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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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From Hypergraph Energy Functions to Hypergraph Neural Networks
, 2023 Hypergraphs are a powerful abstraction for representing higher-order interactions between entities of interest. To exploit these relationships in making downstream predictions, a variety of hypergraph neural network architectures have recently been proposed, in large part building upon precursors from the more traditional graph neural network (GNN ...
Wang, Yuxin +4 more
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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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Supervised Reinforcement Session Recommendation Model Based on Dual-Graph Convolution
IEEE Access, 2023 In the field of session-based recommendation by anonymous sessions, the commonly used supervised learning modeling method has the problem of sub-optimal recommendation.
Shunpan Liang +2 more
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T-HyperGNNs: Hypergraph Neural Networks Via Tensor Representations
IEEE Transactions on Neural Networks and Learning Systems, 2023 <p>Hypergraph neural networks (HyperGNNs) are a family of deep neural networks designed to perform inference on hypergraphs. HyperGNNs follow either a spectral or a spatial approach, in which a convolution or message-passing operation is conducted based on a hypergraph algebraic descriptor.
Fuli Wang +3 more
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Academic team formation as evolving hypergraphs [PDF]
, 2010 This paper quantitatively explores the social and socio-semantic patterns of constitution of academic collaboration teams. To this end, we broadly underline two critical features of social networks of knowledge-based collaboration: first, they ...
A. J. Lott +55 more
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