将其处理为dglgraph的形式: data_dict={('queue','queue_to_link','link'):(x['queue_to_link'].to(torch.int32),x['sequence_links'].to(torch.int32)),('path','path_to_queue','queue'):(x['path_to_queue'].to(torch.int32),x['sequence_queues'].to(torch.int32)),('queue','qu...
二是基于网络的方法(network-based),利用药物-蛋白的关联网络,根据目标关联的药物和蛋白预测相互作用。原理是如果两个蛋白关联的结构相似,其中一个可以与药物相互作用,另一个也可以与药物作用。这种方法通常需要构建一个包含现有药物和蛋白质的网络,并计算药物对和蛋白质对的相似性得分。缺点是比较依赖相似性得分的质量...
文章于2020年七月发表在IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING上,第一作者为范文琪,近几年主要研究方向为graph,social recommendat,llm等,有多篇结合图神经网络进行社交分析的文章。作者介绍 1.概述 社交网络、用户购物行为、物品间关系等许多现实应用中的数据都可以用图来表示。图神经网络( Graph Neur...
Graph Neural Networks (GNNs) have achieved state-of-the-art performance in many fields and attracted a lot of attention in the communit. Most Graph Neural Networks can be merely used when graph-structured data is available. However, many graph structures have noise, or data itself has no gra...
Neural Network for Graphs: A Contextual Constructive Approach 来自 Semantic Scholar 喜欢 0 阅读量: 1511 作者: A Micheli 摘要: This paper presents a new approach for learning in structured domains (SDs) using a constructive neural network for graphs (NN4G). The new model allows the ...
为了解决样本数量远少于特征数量的“n << p”问题,并设计一个不依赖外部知识的分类模型,本文提出了一个森林图嵌入深度前馈网络(forgeNet)模型。该模型将 GEDFN 架构与森林特征图提取器集成在一起,从而可以以监督的方式学习特征图并为给定的任务构建特征图。为了验证该方法的能力,本文用合成数据集和真实数据集对 fo...
In this paper, we propose a graph neural network-based bearing fault detection method in order to improve the accuracy of bearing fault detection. Our main contributions are summarized as follows: 1. We convert the time-series signal of vibration into non-Euclidean structured graph data by ...
graph neural network (GNN) framework, to describe functional interactions based on the structural anatomical layout. A GNN allows us to process graph-structured spatio-temporal signals, providing a possibility to combine structural information derived from diffusion tensor imaging (DTI) with temporal ...
Selective changes of resting-state networks in individuals at risk for Alzheimer's disease Alzheimer's disease (AD) is a neurodegenerative disorder that prominently affects cerebral connectivity. Assessing the functional connectivity at rest, rec... C Sorg,V Riedl,Mark Muehlau,... - 《Proceedings...
据我们所知,TactileSignet是第一个用于触觉数据的事件驱动图神经网络。一个相关的模型是最近提出的TactileGCN[16],它使用图卷积网络(GCN)[17]进行触觉对象识别。这项工作的关键区别在于,TactileSignet是事件驱动的(带有尖峰神经元),我们利用了拓扑自适应图卷积网络(TAGCN)[18];此前已证明,TAGCN具有优异的性能,同时...