当前大多数研究工作表明,基于GNN的恶意域名检测方法最为有效。此类方法首先基于DNS日志等数据构建DMG (Domain maliciousness graph),之后训练GNN模型根据图上已知恶意域名推断其它恶意域名。由于此类方法依赖DMG,给攻击者留出了空间,通过篡改属性、边等信息进行对抗攻击。本文首次提出一种多样本逃逸攻击(multi-instance evasio...
In this chapter we will review the existing biomedical KG and introduce how GNN techniques can facilitate the D 3 process on the KG. We will also introduce two case studies on Parkinson's disease and COVID-19, and point out future directions....
“Implicit Latent Variable Model for Scene-Consistent Motion Forecasting“ 本文试图理解城市交通的运动预测,特别对今后轨迹的联合分布通过一个隐式latent variable模型(ILVM)定义,这样采用交互图对场景建模,然后采用GNN学习一个分布的场景latent representation。 本文是基于给定actors的真实过去轨迹去预测多agent轨迹预测。
data-driven motivation. For classification, we considered data of each subject as a graph, with temporal features as node features and spatial features as edge weights. The graphs were fed into GNNs for training and testing. Experimental results showed that our GNN-based methods realized the best...
GNN-based gene-selection deep learning model for drug response prediction The use of drug and genomic data in drug response prediction poses a significant challenge due to the high number of genomic features. Coding genes alone often surpass 20,000, which can lead to overfitting and performance ...
8Branches Tags Code README MIT license RecHub A library for GNN-based recommendation system. Models ModelFull nameTypePaper NCFNeural Collaborative FilteringNon-graphhttps://arxiv.org/abs/1708.05031 GCNGraph Convolutional NetworksHomogeneous graphhttps://arxiv.org/abs/1609.02907 ...
Graph-based fraud detection approaches have escalated lots of attention recently due to the abundant relational information of graph-structured data, which may be beneficial for the detection of fraudsters. However, the GNN-based algorithms could fare poorly when the label distribution of nodes is hea...
Then, we adapt a generalizable approximate Graph Partitioning framework which leverages on Graph Neural Network (GNN) to embed the RAN network spacial feature and on Multilayer Perceptron (MLP) for graph partitioning. Based on the framework, we propose a MEC server planning algorithm named MECP-...
这是我在学习李宏毅老师机器学习课程时记录的笔记,并不是一个全面的记录而只记录我认为比较关键的知识点,起到知识梳理和温故知新的作用。对较为简单的点只放上PPT和一点记录,对自认为重点的内容会多记录一些理解。 首发于个人公众号“皮皮嬉”。 1
GNN可以有多层,在计算得到每层各节点的隐层特征表示之后,进行readout,也就是得到这个图整体的最终特征表示。 NN4G就是将各层的节点的隐层表示相加求平均MEAN(Hi)之后,得到这一层的隐层表示,然后将各层的隐层表示进行加权,得到这个图最终的特征表示。 2、DCNN 和NN4G一样的input layer 不一样的是,hidden laye...