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Hypergraph Convolutional Recurrent Neural Network
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2020In this study, we present a hypergraph convolutional recurrent neural network (HGC-RNN), which is a prediction model for structured time-series sensor network data. Representing sensor networks in a graph structure is useful for expressing structural relationships among sensors.
Jaehyuk Yi, Jinkyoo Park
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Mode Hypergraph Neural Network
IEEE Transactions on Neural Networks and Learning SystemsThe hypergraph neural network (HGNN) is an emerging powerful tool for modeling and learning complex, high-order correlations among entities upon hypergraph structures. While existing HGNN-based approaches excel in modeling high-order correlations among data using hyperedges, they often have difficulties in distinguishing diverse semantics ( e.g ...
Shuyi Ji +4 more
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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
NeurocomputingYuge Wang +4 more
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Hypergraphs: Organizing complex natural neural networks
2005 3rd International Conference on Intelligent Sensing and Information Processing, 2005Data from neuroscience research has shown that the brain can be studied as a neural network. In view of the brain's seemingly infinite complexity, we organize the entire network into a series of sub-networks, each of whose functionalities combine to become the knowledge representation capability of the entire network.
null Eakta Jain +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 Networks for Hypergraph Matching
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021Xiaowei Liao, Yong Xu, Haibin Ling
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Hypergraph Neural Network Hawkes Process
2022 International Joint Conference on Neural Networks (IJCNN), 2022Zi-Hao Cheng, Jian-Wei Liu, Ze Cao
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Deep Hypergraph Neural Networks with Tight Framelets
Proceedings of the AAAI Conference on Artificial IntelligenceHypergraphs provide a flexible framework for modeling high-order (complex) interactions among multiple entities, extending beyond traditional pairwise correlations in graph structures. However, deep hypergraph neural networks (HGNNs) often face the challenge of oversmoothing with increasing depth, similar to issues in graph neural networks (GNNs ...
Ming Li +6 more
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