To effectively address those issues, a hierarchical adaptive multi-scale hypergraph attention convolution network (HAM-HGNet) is proposed in our work. Firstly, a hierarchical adaptive clustering partition module
In this section, we evaluate the proposed hypergraph convolution and hypergraph attention in the task of semi-supervised node classification. Following [22], [31], we first employ three citation network datasets, including the Cora, Citeseer and Pubmed datasets [53], to make a fair comparison ...
Efficient Cooperation Strategy Generation in Multi-Agent Video Games via Hypergraph Neural Network Value Function Factorisation with Hypergraph Convolution for Cooperative Multi-agent Reinforcement Learning PyG库中HypergraphConv类的使用 PyG库的官方资料 HypergraphConv类的用法 例子 其他参考资料 AAAI2019论文的代码...
Besides the backbone network consisting of spectral hypergraph convolution blocks, a hyperedge attention module is learned to adjust the weights of hyperedges in the WHCN. Finally, a segmentation network is trained by these pseudo point cloud labels. We comprehensively conduct experiments on the ...
In the Dynamic Graph Temporal Convolution Module (DGTCM), we introduce the Dynamic Multi-Order Graph Convolution Network (D-MGCN), inspired by Graph WaveNet [12]. This structure effectively captures both spatial and temporal dimensions of traffic data and is implemented as detailed in formula (19...
HNHN is a hypergraph convolution network with nonlinear activation functions applied to both hypernodes and hyperedges, combined with a normalization scheme that can flexibly adjust the importance of high-cardinality hyperedges and high-degree vertices depending on the dataset. We demonstrate improved ...
PyTorch Geometric: pytorch-geometric.readthedocs.io (Hypergraph Convolution Network) DeepHypergraph: github.com/iMoonLab/Dee (Hypergraph Neural Networks) OpenHGNN: github.com/BUPT-GAMMA/O (Heterogeneous Graph Neural Network) HyperNetX: github.com/pnnl/HyperNe (Community Detection, Clustering, Generation,...
这里分为 Interest-based User和 Item两种构建方式,如上图的下半部分。...超图卷积(Hypergraph Convolution Network (HGCN))。构完超图之后,学习表示就套公式就好: 预测模块。...总结来说HyperCTR关键词是多模态+时序+组,通过基于兴趣的用户超图和项超图这两个Hypergraph来丰富每个用户和项的表示。
A novel hypergraph convolution network-based approach for predicting the material removal rate in chemical mechanical planarization J Intell Manuf, 33 (8) (2022), pp. 2295-2306 CrossrefView in ScopusGoogle Scholar [99] T. Wu, Q. Ling Self-supervised heterogeneous hypergraph network for knowledge...
ViHGNN(Vision HyperGraph Neural Network)是一种基于超图的模型。它通过传统的聚类算法(clustering algorithm)构建超图,并使用多层超图卷积(HyperGraph Convolution, HGConv)进行表示学习(representation learning)。 HGConv擅长处理局部结构和拓扑关系,但在全局信息聚合方面存在不足。 Transformer虽然能够捕捉全局信息,但缺乏对...