论文名称:IJCAI-2019-Dynamic Hypergraph Neural Networks 论文地址: https://www.ijcai.org/proceedings/2019/0366.pdfwww.ijcai.org/proceedings/2019/0366.pdf 摘要 在神经网络模型中,由网络深层生成的嵌入特征具有初始结构无法捕获的高阶关系。现有的基于图或超图的神经网络的主要缺点是只采用初始的图或超图结构...
In this paper, we present a hypergraph neural networks (HGNN) framework for data representation learning, which can encode high-order data correlation in a hypergraph structure. Confronting the challenges of learning representation for complex data in real practice, we propose to incorporate such data...
【归纳综述】Graph Neural Network: An Introduction Ⅰ 刘浚嘉发表于RL in... CS224W-图神经网络笔记1:Introduction : Structure of Graphs Jarden 《Deep Learning on Graphs: A Survey》分享 引言: 图神经网络作为一种愈发火热的机器学习技术,在很多的领域展现出了独特的作用力。本人在研一的主要研究方向是 服务...
Recently, the hypergraph neural network (HGNN) has drawn increasing attention in modeling complex high-order correlations. Compared to simple graph neural networks, HGNNs exhibit more powerful representational ability. There are two limitations in the application of hypergraph theory to hyperspectral image...
we propose HyperGraph neural network for ERE ($hgnn{}$), which is built upon the PL-marker (a state-of-the-art marker-based pipleline model). To alleviate error propagation,we use a high-recall pruner mechanism to transfer the burden of entity identification and labeling from the NER modul...
To address this problem, Dynamic Hypergraph Neural Networks based on Key Hyperedges (DHKH) model is proposed in this paper. Considering that the graph structure data in the real world is not uniformly distributed both semantically and...
Recently, graph neural networks have attracted great attention and achieved prominent performance in various research fields. Most of those algorithms have assumed pairwise relationships of objects of interest. However, in many real applications, the relationships between objects are in higher-order, beyo...
GNN:Session-based Recommendation with Graph Neural Networks简介 Session-based Recommendation with Graph Neural Networks 摘要 作者提出SR-GNN,将session序列建模为图结构数据。在session图的...,忽视了items之间转换时的上下文。 同时指出GNN能很好地生成items嵌入向量,以此来说明提出的SR-GNN更好。 主要贡献: 将...
Recently, graph-based neural networks have been investigated in hyperspectral image (HSI) classification to address the limited global feature representati... Q Xu,J Lin,B Jiang,... - 《Neural Computing & Applications》 被引量: 0发表: 2023年 SHCNet: A semi-supervised hypergraph convolutional ...
HGNN+: General Hypergraph Neural Networks A few hypergraph-based methods have recently been proposed to address the problem of multi-modal/multi-type data correlation by directly concatenating the ... Y Gao,Y Feng,JR Ji - 《IEEE Transactions on Pattern Analysis & Machine Intelligence》 被引量:...