Directed hypergraph neural network
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Abstract (arXiv)
To deal with irregular data structure, graph convolution neural networks have been developed by a lot of data scientists. However, data scientists just have concentrated primarily on developing deep neural network method for un-directed graph. In this paper, we will present the novel neural network method for directed hypergraph. In the other words, we will develop not only the novel directed hypergraph neural network method but also the novel directed hypergraph based semi-supervised learning method. These methods are employed to solve the node classification task. The two datasets that are used in the experiments are the cora and the citeseer datasets. Among the classic directed graph based semi-supervised learning method, the novel directed hypergraph based semi-supervised learning method, the novel directed hypergraph neural network method that are utilized to solve this node classification task, we recognize that the novel directed hypergraph neural network achieves the highest accuracies.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Aug 2020.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 1; 2024: 2.
6 papers.
- 2024A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guidecited by 22
- 2022Graph Neural Networks Designed for Different Graph Types: A Surveycited by 21
- 2021Text classification problems via BERT embedding method and graph convolutional neural networkcited by 2
- 2022VAC2: Visual Analysis of Combined Causality in Event Sequencescited by 2
- 2023Momentum Gradient-based Untargeted Attack on Hypergraph Neural Networkscited by 1
- 2024Hypergraph Laplacian Eigenmaps and Face Recognition Problemscited by 1
- 2024Hypergraph Laplacian Eigenmaps and Face Recognition Problems27 May 2024
- 2024A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide1 Apr 2024
- 2023Momentum Gradient-based Untargeted Attack on Hypergraph Neural Networks24 Oct 2023
- 2022VAC2: Visual Analysis of Combined Causality in Event Sequences11 Jun 2022
- 2022Graph Neural Networks Designed for Different Graph Types: A Survey6 Apr 2022
- 2021Text classification problems via BERT embedding method and graph convolutional neural network30 Nov 2021