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...
代码地址: GitHub - SenseTime-Knowledge-Mining/BridgeDPI: BridgeDPI: A Novel Graph Neural Network for Predicting Drug-Protein Interactions 数据地址: BindingDB数据集: GitHub - IBM/InterpretableDTIP: InterpretableDTIP C.ELEGANS和HUMAN数据集: GitHub - masashitsubaki/CPI_prediction: This is a code for...
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 extension of the input domain for supervised neural networks to a general class of graphs including both acyclic/cyclic, directed/undirected...
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...
Deep Convolutional Networks on Graph-Structured Data:谱域 Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering:谱域 Semi-Supervised Classification with Graph Convolutional Networks:谱域 空域论文# Neural Network for Graphs: A Contextual Constructive Approach:空域图卷积早期代表作品 ...
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) is effective in modeling high-order interactions and has been widely used in various personalized applications such as recommendation. However, mainstream personalization methods rely on centralized GNN learning on global graph
在这项工作中,我们介绍了一种基于词典的图神经网络lexicon-based graph neural network(LGN),它实现了中文NER作为节点分类任务。该模型打破了RNN的串行化处理结构,通过仔细的连接,字符和单词之间的交互效果更好。词汇知识将相关字符连接起来,以捕获本地成分。同时,设计了一个全局中继节点来捕获远程依赖性和高级特性。LG...
GraphProt2, a computational RBP binding site prediction framework based on graph convolutional neural networks (GCNs). In contrast to current CNN methods, GraphProt2 offers native support for the encoding of base pair information as well as variable length input, providing increased flexibility and ...
图自编码器 (graph autoencoders, GAE) 考虑时间因素的图神经网络 (spatial-temporal graph neural networks, ST-GNN) 讨论图神经网络在各个领域的应用 总结了 GNN 的开源代码、基准数据集和模型评估 潜在的研究方向 介绍 机器学习解决的任务 【严重依赖于工人数据标注】 ...