前言 论文链接:https://arxiv.org/abs/1901.08150 1. Hypergraph Convolution and Hypergraph Attention 1.1 Hypergraph Revisited 一个普通图定义为 G = ( V , E ) \mathcal{G}=(V,E) G=(V,E) ,其中节点集定义为 V = { v 1 , v 2 , &helli... 查看原
In this section, we first give the definition of hypergraph in Section 3.1, then elaborate the proposed hypergraph convolution and hypergraph attention in Section 3.2 and Section 3.3, respectively. At last, Section 3.4 provides a deeper analysis of the properties of our methods. Experiments In this...
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...
(LHCN)Line Hypergraph Convolution Network(2020)笔记 (G)是否有连接是由G中边是否有公共顶点所决定。 将一个超图H=(V,E)转化成一个带权线图,跟前面的一样,超边为L(H)节点,如果超边有公共点,就认为L(H)的节点有连接。线图边的权值由其两个顶点所...,我们取其所属的所有超边的平均表示。 实验我们将...
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,...
Under such circumstances, the spectral-based hypergraph convolution takes the same form as the graph convolution in a GCN [46]. In essence, the HGNN can effectively address pairwise correlations in simple graphs while also capturing and modeling the high-order correlations inherent in hypergraphs....
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。
As opposed to hypergraph convolution, where the underlying structure is defined beforehand, Bai et al. [57] proposed a hypergraph attention mechanism strategy to learn a dynamic connection of hyperedges, which propagates and gathers information in the task-relevant parts of the graph, thereby ...
Formula (13) describes the hypergraph convolution process. Dhe∈RN×N and Dhv∈RE×Erepresent the degree diagonal matrices of the hyperedges and hypernodes, respectively. The incidence matrix is denoted by H∈RE×N, while W∈RN×N represents the weighted diagonal matrix of the hyperedges, typi...
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 ...