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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 151–175 of 403 papers

TitleStatusHype
Adversarial Attack on Network Embeddings via Supervised Network PoisoningCode0
Multiplex Bipartite Network Embedding using Dual Hypergraph Convolutional NetworksCode1
Learning multi-resolution representations of research patterns in bibliographic networksCode0
NEMR: Network Embedding on Metric of Relation—0
Exact Recovery of Community Structures Using DeepWalk and Node2vec—0
JITuNE: Just-In-Time Hyperparameter Tuning for Network Embedding Algorithms—0
Heterogeneous Network Embedding for Deep Semantic Relevance Match in E-commerce Search—0
SDGNN: Learning Node Representation for Signed Directed NetworksCode1
Signed Graph Diffusion Network—0
GAHNE: Graph-Aggregated Heterogeneous Network Embedding—0
Unifying Homophily and Heterophily Network Transformation via Motifs—0
Exploiting Node Content for Multiview Graph Convolutional Network and Adversarial RegularizationCode0
Adversarial Attacks on Deep Graph Matching—0
User-based Network Embedding for Collective Opinion Spammer Detection—0
Multi-View Dynamic Heterogeneous Information Network Embedding—0
Toward Edge-Centric Network Embeddings—0
Embedding Node Structural Role Identity into Hyperbolic Space—0
Introducing various Semantic Models for Amharic: Experimentation and Evaluation with multiple Tasks and DatasetsCode1
Identifying Transition States of Chemical Kinetic Systems using Network Embedding Techniques—0
Deep Kernel Supervised Hashing for Node Classification in Structural Networks—0
Learning to Embed Categorical Features without Embedding Tables for Recommendation—0
TriNE: Network Representation Learning for Tripartite Heterogeneous Networks—0
Inductive Graph Embeddings through Locality Encodings—0
EPNE: Evolutionary Pattern Preserving Network Embedding—0
Sub-graph Contrast for Scalable Self-Supervised Graph Representation LearningCode1
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