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Network Embedding

Network Embedding, also known as "Network Representation Learning", is a collective term for techniques for mapping graph nodes to vectors of real numbers in a multidimensional space. To be useful, a good embedding should preserve the structure of the graph. The vectors can then be used as input to various network and graph analysis tasks, such as link prediction

Source: Tutorial on NLP-Inspired Network Embedding

Papers

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Showing 376–400 of 403 papers

TitleStatusHype
Domain-adversarial Network AlignmentCode0
Learning Vertex Representations for Bipartite NetworksCode0
Deep Node Ranking for Neuro-symbolic Structural Node Embedding and ClassificationCode0
LNEMLC: Label Network Embeddings for Multi-Label ClassificationCode0
Deep Network Embedding for Graph Representation Learning in Signed NetworksCode0
Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via RankingCode0
DeBayes: a Bayesian Method for Debiasing Network EmbeddingsCode0
Simultaneous Weight and Architecture Optimization for Neural NetworksCode0
BHGNN-RT: Network embedding for directed heterogeneous graphsCode0
Are Graph Embeddings the Panacea? An Empirical Survey from the Data Fitness PerspectiveCode0
metapath2vec: Scalable Representation Learning for Heterogeneous NetworksCode0
TextCNN with Attention for Text ClassificationCode0
Data driven approximation of parametrized PDEs by Reduced Basis and Neural NetworksCode0
DANES: Deep Neural Network Ensemble Architecture for Social and Textual Context-aware Fake News DetectionCode0
mSHINE: A Multiple-meta-paths Simultaneous Learning Framework for Heterogeneous Information Network EmbeddingCode0
Where are we in embedding spaces? A Comprehensive Analysis on Network Embedding Approaches for Recommender SystemsCode0
Vertex-reinforced Random Walk for Network EmbeddingCode0
Vaccine skepticism detection by network embeddingCode0
MGCN: Semi-supervised Classification in Multi-layer Graphs with Graph Convolutional NetworksCode0
Multi-Level Network Embedding with Boosted Low-Rank Matrix ApproximationCode0
Relation order histograms as a network embedding toolCode0
Splitter: Learning Node Representations that Capture Multiple Social ContextsCode0
CSNE: Conditional Signed Network EmbeddingCode0
Cross-Network Social User Embedding with Hybrid Differential Privacy GuaranteesCode0
Multi-Relation Aware Temporal Interaction Network EmbeddingCode0
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