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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 1–50 of 403 papers

TitleStatusHype
FlagVNE: A Flexible and Generalizable Reinforcement Learning Framework for Network Resource AllocationCode2
Joint Admission Control and Resource Allocation of Virtual Network Embedding via Hierarchical Deep Reinforcement LearningCode2
ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement LearningCode1
Mutual Contrastive Learning for Visual Representation LearningCode1
Robust Dynamic Network Embedding via EnsemblesCode1
Sub-graph Contrast for Scalable Self-Supervised Graph Representation LearningCode1
Introducing various Semantic Models for Amharic: Experimentation and Evaluation with multiple Tasks and DatasetsCode1
Fast Sequence-Based Embedding with Diffusion GraphsCode1
Machine Learning on Graphs: A Model and Comprehensive TaxonomyCode1
Multi-View Collaborative Network EmbeddingCode1
Outlier Aware Network Embedding for Attributed NetworksCode1
Random Walk on Multiple NetworksCode1
Signed Graph Attention NetworksCode1
Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic GraphsCode1
Fast Graph Learning with Unique Optimal SolutionsCode1
Adversarial Privacy Preserving Graph Embedding against Inference AttackCode1
Heterogeneous Network Representation Learning: A Unified Framework with Survey and BenchmarkCode1
Inductive Document Network Embedding with Topic-Word AttentionCode1
LINE: Large-scale Information Network EmbeddingCode1
LouvainNE: Hierarchical Louvain Method for High Quality and Scalable Network EmbeddingCode1
Monkey Business: Reinforcement learning meets neighborhood search for Virtual Network EmbeddingCode1
MultiVERSE: a multiplex and multiplex-heterogeneous network embedding approachCode1
Network Together: Node Classification via Cross-Network Deep Network EmbeddingCode1
Online Knowledge Distillation via Mutual Contrastive Learning for Visual RecognitionCode1
Adversarial Deep Network Embedding for Cross-network Node ClassificationCode1
DynWalks: Global Topology and Recent Changes Awareness Dynamic Network EmbeddingCode1
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
Fast Network Embedding Enhancement via High Order Proximity ApproximationCode1
Network Embedding with Completely-imbalanced LabelsCode1
DANE: Domain Adaptive Network EmbeddingCode1
Fast Sequence Based Embedding with Diffusion GraphsCode1
Adversarial Training Methods for Network EmbeddingCode1
GloDyNE: Global Topology Preserving Dynamic Network EmbeddingCode1
HiGitClass: Keyword-Driven Hierarchical Classification of GitHub RepositoriesCode1
ImGAGN:Imbalanced Network Embedding via Generative Adversarial Graph NetworksCode1
Adaptive Graph Auto-Encoder for General Data ClusteringCode1
Learning Semantic Relationship Among Instances for Image-Text MatchingCode1
LouvainNE: Hierarchical Louvain Method for High Quality and Scalable Network Embedding.Code1
A Survey on Role-Oriented Network EmbeddingCode1
Representation Learning for Attributed Multiplex Heterogeneous NetworkCode1
Modeling Dynamic Heterogeneous Network for Link Prediction using Hierarchical Attention with Temporal RNNCode1
Multiplex Bipartite Network Embedding using Dual Hypergraph Convolutional NetworksCode1
Multiplex Heterogeneous Graph Convolutional NetworkCode1
Fast and Accurate Network Embeddings via Very Sparse Random ProjectionCode1
Discrete-time Temporal Network Embedding via Implicit Hierarchical Learning in Hyperbolic SpaceCode1
Node Classification on Graphs with Few-Shot Novel Labels via Meta Transformed Network EmbeddingCode1
Unsupervised Differentiable Multi-aspect Network EmbeddingCode1
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