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 451–460 of 1192 papers

TitleStatusHype
Transforming Graphs for Enhanced Attribute Clustering: An Innovative Graph Transformer-Based Method—0
GPINN: Physics-informed Neural Network with Graph EmbeddingCode0
Contextual Dictionary Lookup for Knowledge Graph Completion—0
MTS2Graph: Interpretable Multivariate Time Series Classification with Temporal Evolving Graphs—0
ATEM: A Topic Evolution Model for the Detection of Emerging Topics in Scientific Archives—0
HetReGAT-FC: heterogeneous residual graph attention network via feature completionCode0
Semantic tradeoff for heterogeneous graph embedding—0
Causal Intervention for Measuring Confidence in Drug-Target Interaction Prediction—0
Knowledge Graph Embeddings in the Biomedical Domain: Are They Useful? A Look at Link Prediction, Rule Learning, and Downstream Polypharmacy TasksCode0
Knowledge Graph Embedding with Electronic Health Records Data via Latent Graphical Block Model—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified