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 671–680 of 1192 papers

TitleStatusHype
GenURL: A General Framework for Unsupervised Representation Learning—0
Unbiased Graph Embedding with Biased Graph Observations—0
Degree-Based Random Walk Approach for Graph Embedding—0
SGEN: Single-cell Sequencing Graph Self-supervised Embedding Network—0
Residual2Vec: Debiasing graph embedding with random graphsCode0
Scalable Graph Embedding LearningOn A Single GPU—0
Fast Attributed Graph Embedding via Density of StatesCode0
Hybrid Graph Embedding Techniques in Estimated Time of Arrival Task—0
Is There More Pattern in Knowledge Graph? Exploring Proximity Pattern for Knowledge Graph Embedding—0
Why does Negative Sampling not Work Well? Analysis of Convexity in Negative Sampling—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified