Graph convolutional network (GCN), with its capability to update the current node features according to the features of its first-order adjacent nodes and edges, has achieved impressive performance in dependency capturing. But some important nodes from which we should figure out the dependencies are...
(下面介绍加权图卷积网络WGCN,Weighted graph convolutional network.) WGCN与vanilla GCN的对比 图3,WGCN与vanilla GCN的对比。以上左图中的节点a为例。一开始,节点a仅包含其本身的特征。在1层GCN之后,如上右图所示,节点a获得邻接节点c,h和i的特征。同时,节点c的信息也由其邻接节点的特征更新,如节点h和i。在...
为了解决这些问题,我们提出了一种新的加权图卷积网络模型weighted graph convolutional network model(WGCN)。在该模型中,我们在依赖树中加入虚边virtual edges 来构造一个逻辑邻接矩阵 logical adjacency matrix(LAM),它只需要一层WGCN就可以直接求出k阶邻域依赖k-order neighborhood dependence。我们利用WGCN层间的残差...
To overcome this limitation and achieve robust PolSAR image classification, this paper proposes the multi-scale evolving weighted graph convolutional network (MEWGCN), where weighted graphs based on superpixel technique and Wishart-derived distance are constructed to enable efficient handling of graphical ...
This paper proposes a novel weighted graph convolutional network by constructing a logical adjacency matrix which effectively solves the feature fusion of multi-hop relation without additional layers and parameters for relation extraction task. Experimental results show that our model can take better advant...
Drug repositioning based on weighted local information augmented graph neural network.pdf 1.6M· 百度网盘 Drug repositioning with adaptive graph convolutional networks.docx 1.3M· 百度网盘 摘要 药物重新定位是将现有药物重新定向到新的治疗目的的策略,对于加速药物发现至关重要。虽然许多研究都致力于对复杂的药物...
图神经网络(Graph Neural Network,GNN)是指使用神经网络来学习图结构数据,提取和发掘图结构数据中的特征和模式,在药物研发,脑科学,生命科学,社交网络等领域得到了广泛... 张文川,计算机科学与技术 - 《贵州师范大学》 被引量: 0发表: 0年 Knowledge Graph Convolutional Network with Heuristic Search for Drug Repo...
Gcns-net: a graph convolutional neural network approach for decoding time-resolved eeg motor imagery signals. IEEE Trans. Neural Netw. Learn. Syst. 1–12. https://doi.org/10.1109/TNNLS.2022.3202569 (2022). Hou, Y. et al. Deep feature mining via the attention-based bidirectional long short ...
An optimized graph-based structure for single-cell RNA-seq cell-type classification based on non-linear dimension reduction Saeedeh Akbari Rokn Abadi Seyed Pouria Laghaee Somayyeh Koohi BMC Genomics(2023) Co-embedding of edges and nodes with deep graph convolutional neural networks ...
Moreover, we define the complementary graph and alpha centrality of weighted network. Correspondingly, several synthetic and real-world networks are used to verify the effectiveness of the WD-metric. Experimental results show that WD-metric can effectively capture the influence of weight on the ...