深读

2023-01-12【论文阅读｜深读】GAS：Role-Oriented Graph Auto-encoder Guided by Structural Information
目录前言简介Abstract1Introduction2RelatedWork3Method3.1Notations3.2FeatureExtraction3
2023-01-12【论文阅读｜深读】 GraphSAGE：Inductive Representation Learning on Large Graphs
目录前言简介Abstract1Introduction2Relatedwork3Proposedmethod:GraphSAGE3.1Embeddinggeneration(i.e.,
2023-01-12【论文阅读｜深读】RolNE: Improving the Quality of Network Embedding with Structural Role Proximity
目录前言简介Abstract1Introduction2RelatedWork3RolNE4ExperimentalEstimate4.1BarbellGraph
2023-01-12【论文阅读｜深读】DANE:Deep Attributed Network Embedding
目录前言Abstract1Introduction2RelatedWorks2.1PlainNetworkEmbedding2.2AttributedNetworkEmbedding3De
2023-01-12【论文阅读｜深读】Role2Vec:Role-Based Graph Embeddings
目录前言Abstract1INTRODUCTION2FRAMEWORK2.1MappingVerticestoVertex-Roles顶点映射到顶点角色2.2AttributedRando
2023-01-12【论文阅读｜深读】SDNE:Structural Deep Network Embedding
目录前言ABSTRACT1.INTRODUCTION2.RELATEDWORK2.1DeepNeuralNetwork2.2NetworkEmbedding3.STRUCTURALDEEP
2023-01-12【论文阅读｜深读】Net2Net-NE：Learning Network-to-Network Model for Content-rich Network Embedding
目录前言简介ABSTRACT1INTRODUCTION2RELATEDWORK3PROBLEMFORMULATION4METHODOLOGY4.1ContentEmbedd