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Hypergraph analysis of neural networks
Physica D: Nonlinear Phenomena, 1989zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jeffries, Clark, van den Driessche, P.
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Purity Skeleton Dynamic Hypergraph Neural Network
NeurocomputingXibei Yang, Qiguo Sun, Yuhua Qian
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Hypergraph Neural Networks for Hypergraph Matching
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021Xiaowei Liao, Yong Xu 0007, Haibin Ling
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HGNNv2: Stable Hypergraph Neural Networks
IEEE Transactions on Pattern Analysis and Machine IntelligenceHypergraph neural networks (HGNNs) are widely used models for analyzing higher-order relational data. HGNNs suffer from the rapid performance degradation with increasing layers. Hypergraph dynamic system (HDS) is a potential way to deal with this challenge.
Yue Gao 0002 +6 more
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Hypergraphs and Neural Networks
1991It is certainly desirable to have mathematically rigorous knowledge of the attractors of neural network models. In fact, for those models to be used in content addressable memory (static memories) or robot control, one usually seeks some assurance that the only attractors are constant trajectories built into the model and in particular that no limit ...
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Hypergraph Neural Network Hawkes Process
2022 International Joint Conference on Neural Networks (IJCNN), 2022Zi-Hao Cheng, Jian-Wei Liu 0006, Ze Cao
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Hypergraph Neural Network for Emotion Recognition in Conversations
ACM Transactions on Asian and Low-Resource Language Information ProcessingModeling conversational context is an essential step for emotion recognition in conversations. Existing works still suffer from insufficient utilization of local context information and remote context information. This article designs a hypergraph neural network, namely HNN-ERC, to better utilize local and remote contextual information.
Cheng Zheng 0006 +2 more
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HGNN+: General Hypergraph Neural Networks
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023Yue Gao, Yifan Feng, Shuyi Ji
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Measurement: Journal of the International Measurement Confederation, 2022
Hongkun Li, Shunxin Cao
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Hongkun Li, Shunxin Cao
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Dynamic hypergraph neural networks based on key hyperedges
Information Sciences, 2022Xiaojun Kang, Hong Yao, Shihua Qi
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