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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 51–75 of 403 papers

TitleStatusHype
Zoo Guide to Network Embedding—0
H^2TNE: Temporal Heterogeneous Information Network Embedding in Hyperbolic SpacesCode0
Space-Invariant Projection in Streaming Network Embedding—0
DANES: Deep Neural Network Ensemble Architecture for Social and Textual Context-aware Fake News DetectionCode0
Learning Semantic Relationship Among Instances for Image-Text MatchingCode1
Cross Version Defect Prediction with Class Dependency Embeddings—0
Author Name Disambiguation via Heterogeneous Network Embedding from Structural and Semantic Perspectives—0
Recommending on graphs: a comprehensive review from a data perspective—0
A Model-data-driven Network Embedding Multidimensional Features for Tomographic SAR Imaging—0
An Isolation-Aware Online Virtual Network Embedding via Deep Reinforcement Learning—0
DyCSC: Modeling the Evolutionary Process of Dynamic Networks Based on Cluster StructureCode0
ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement LearningCode1
Embedding Representation of Academic Heterogeneous Information Networks Based on Federated Learning—0
Attributed Network Embedding Model for Exposing COVID-19 Spread Trajectory Archetypes—0
Cross-Network Social User Embedding with Hybrid Differential Privacy GuaranteesCode0
Associative Learning for Network Embedding—0
Multiplex Heterogeneous Graph Convolutional NetworkCode1
Online Knowledge Distillation via Mutual Contrastive Learning for Visual RecognitionCode1
Signed Network Embedding with Application to Simultaneous Detection of Communities and Anomalies—0
Large-Scale Privacy-Preserving Network Embedding against Private Link Inference Attacks—0
NECA: Network-Embedded Deep Representation Learning for Categorical Data—0
Unsupervised Network Embedding Beyond HomophilyCode1
Deep Partial Multiplex Network Embedding—0
Pay Attention to Relations: Multi-embeddings for Attributed Multiplex Networks—0
Monkey Business: Reinforcement learning meets neighborhood search for Virtual Network EmbeddingCode1
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