暂无搜索历史
题目:Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective
题目:User Preference-aware Fake News Detection
题目:Simple and Deep Graph Convolutional Networks
题目: Influence maximization in social networks using graph embedding and graph ne...
题目:Simplifying Graph Convolutional Networks
题目: Information propagation in online social networks: a tie-strength perspectiv...
题目:FANG: Leveraging Social Context for Fake News Detection Using Graph Represent...
题目: Heterogeneous Graph Attention Network
题目: Modeling Relational Data with Graph Convolutional Networks
题目:metapath2vec: Scalable Representation Learning for Heterogeneous Networks
自编码器在图领域有着很多应用,其本质就是编码器获取节点的高级向量表示,然后解码器利用高级向量表示来重建图结构。这篇文章主要介绍Kipf和Welling提出的变分...
会议: International Conference on Learning Representations, 2018
题目:Semi-supervised Graph Embedding for Multi-label Graph Node Classification
题目:Link prediction techniques, applications, and performance: A survey
题目:Link prediction techniques, applications, and performance: A
题目:Inductive Representation Learning on Large Graphs
一开始是打算手写一下GCN,毕竟原理也不是很难,但想了想还是直接调包吧。在使用各种深度学习框架时我们首先需要知道的是框架内的数据结构,因此这篇文章分为两个部分:...
题目:Semi-Supervised Classification with Graph Convolutional Networks
Per-FedAvg的原理请见:arXiv | Per-FedAvg:一种联邦元学习方法。
暂未填写公司和职称