论文标题:Variational Graph Auto-Encoders 论文作者:Thomas Kipf, M. Welling 论文来源:2016, ArXiv 论文地址:download 论文代码:download 1 Introduce 变分自编码器在图上的应用,该框架可以自行参考变分自编码器。 2 Method 变分图自编码器(VGAE ),整体框架如下: ...
Variational Graph Auto-Encodersarxiv.org/pdf/1611.07308.pdf codespaperswithcode.com/paper/variational-graph-auto-encoders 变分图自编码器(VGAE)是一种基于变分自编码器的图结构数据上的无监督学习框架。VGAE利用潜在变量,学习无向图的可解释i安在表示,如下图: Cora数据集上训练的无监督VGAE模型的潜...
Variational graph auto-encoders[J]. NIPS, 2016. 代码地址:github.com/tkipf/gae 图神经网络可以细分为五类:图卷积网络、图注意力网络、图时空网络、图生成网络和图自编码器。其中图卷积和图注意力网络资料较多,本文就不再赘述,这里解读一篇发表在NIPS2016上的经典图自编码器论文。 一、摘要 本文是将变分自...
。 2. Variational Autoencoders 为什么我们需要Variational Autoencoders? Variational Avtoencoder的最大好处是特能够通过原始数据产生新的数据。而传统的Auto encoder只能够通过原始数据产生相似的数据。 主要思想: 它先学习所有的样本的分布,然后根据这个分布随机产生新的样本。 Encoder 以一个点X作为输入,产生均值 和...
variational graph auto-encoder adversarial learning mutual information maximization 摘要 With the success of Graph Neural Network (GNN) in network data, some GNN-based representation learning methods for networks have emerged recently. Variational Graph Autoencoder (VGAE) is a basic GNN framework for ...
In this study, we present a deep learning framework with variational graph auto-encoder for miRNA-disease association prediction (VGAE-MDA). VGAE-MDA first gets the representations of miRNAs and diseases from the heterogeneous networks constructed by miRNA-miRNA similarity, disease-disease similarity,...
We introduce the variational graph auto-encoder (VGAE), a framework for unsupervised learning on graph-structured data based on the variational auto-encoder (VAE). This model makes use of latent variables and is capable of learning interpretable latent representations for undirected graphs. We demons...
而求导可以和 graph 一些展开联系起来，由于贝叶斯推断对应到物理里面就是两点格林函数，每个推断闭环（x ...
从贝叶斯深度学习的角度来看，传统的auto-encoder存在后验分布无法求解的问题(只有在先验和似然共轭的时候...
《Variational Graph Auto-Encoders (VGAE)》T N. Kipf, M Welling [University of Amsterdam] (2016) http://t.cn/Rf9wcYO