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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 26–50 of 403 papers

TitleStatusHype
Outlier Aware Network Embedding for Attributed NetworksCode1
SDGNN: Learning Node Representation for Signed Directed NetworksCode1
Signed Bipartite Graph Neural NetworksCode1
SiReN: Sign-Aware Recommendation Using Graph Neural NetworksCode1
An Influence-based Approach for Root Cause Alarm Discovery in Telecom NetworksCode1
DynWalks: Global Topology and Recent Changes Awareness Dynamic Network EmbeddingCode1
Fast Network Embedding Enhancement via High Order Proximity ApproximationCode1
DANE: Domain Adaptive Network EmbeddingCode1
Fast and Accurate Network Embeddings via Very Sparse Random ProjectionCode1
Adversarial Training Methods for Network EmbeddingCode1
Fast Sequence Based Embedding with Diffusion GraphsCode1
ImGAGN:Imbalanced Network Embedding via Generative Adversarial Graph NetworksCode1
GloDyNE: Global Topology Preserving Dynamic Network EmbeddingCode1
Adaptive Graph Auto-Encoder for General Data ClusteringCode1
Inductive Document Network Embedding with Topic-Word AttentionCode1
MultiVERSE: a multiplex and multiplex-heterogeneous network embedding approachCode1
A Survey on Role-Oriented Network EmbeddingCode1
Representation Learning for Attributed Multiplex Heterogeneous NetworkCode1
LouvainNE: Hierarchical Louvain Method for High Quality and Scalable Network Embedding.Code1
Machine Learning on Graphs: A Model and Comprehensive TaxonomyCode1
Modeling Dynamic Heterogeneous Network for Link Prediction using Hierarchical Attention with Temporal RNNCode1
Multi-View Collaborative Network EmbeddingCode1
Mutual Contrastive Learning for Visual Representation LearningCode1
Network Together: Node Classification via Cross-Network Deep Network EmbeddingCode1
Unsupervised Differentiable Multi-aspect Network EmbeddingCode1
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