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 571–580 of 1192 papers

TitleStatusHype
Improving Out-of-Scope Detection in Intent Classification by Using Embeddings of the Word Graph Space of the Classes—0
Confidence-aware Self-Semantic Distillation on Knowledge Graph Embedding—0
Binarized Graph Neural Network—0
Improving Knowledge Graph Embedding Using Affine Transformations of Entities Corresponding to Each Relation—0
Disentangling Interpretable Generative Parameters of Random and Real-World Graphs—0
Kernel classification of connectomes based on earth mover's distance between graph spectra—0
Incomplete Multi-view Clustering via Graph Regularized Matrix Factorization—0
DualDE: Dually Distilling Knowledge Graph Embedding for Faster and Cheaper Reasoning—0
Improving embedding of graphs with missing data by soft manifolds—0
Adversarial Attack Framework on Graph Embedding Models with Limited Knowledge—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified