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 271–280 of 1192 papers

TitleStatusHype
An Investigation of Evaluation Metrics for Automated Medical Note GenerationCode0
How to Turn Your Knowledge Graph Embeddings into Generative ModelsCode1
3D Rotation and Translation for Hyperbolic Knowledge Graph EmbeddingCode0
Friendly Neighbors: Contextualized Sequence-to-Sequence Link PredictionCode1
HaSa: Hardness and Structure-Aware Contrastive Knowledge Graph EmbeddingCode0
Tight and fast generalization error bound of graph embedding in metric space—0
Semisupervised regression in latent structure networks on unknown manifolds—0
Connector 0.5: A unified framework for graph representation learningCode0
Generating Post-hoc Explanations for Skip-gram-based Node Embeddings by Identifying Important Nodes with Bridgeness—0
Modality-Aware Negative Sampling for Multi-modal Knowledge Graph EmbeddingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified