SOTAVerified

Graph Embedding

Graph embeddings learn a mapping from a network to a vector space, while preserving relevant network properties.

( Image credit: GAT )

Papers

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Showing 1141–1150 of 1192 papers

TitleStatusHype
A Relational Memory-based Embedding Model for Triple Classification and Search PersonalizationCode0
Relation order histograms as a network embedding toolCode0
RelWalk A Latent Variable Model Approach to Knowledge Graph EmbeddingCode0
REMOD: Relation Extraction for Modeling Online DiscourseCode0
Answering Visual-Relational Queries in Web-Extracted Knowledge GraphsCode0
Representation Learning with Weighted Inner Product for Universal Approximation of General SimilaritiesCode0
Repurposing Knowledge Graph Embeddings for Triple Representation via Weak SupervisionCode0
Residual2Vec: Debiasing graph embedding with random graphsCode0
Re-Think and Re-Design Graph Neural Networks in Spaces of Continuous Graph Diffusion FunctionalsCode0
Robustness of graph embedding methods for community detectionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified