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 251–260 of 1192 papers

TitleStatusHype
Re-Think and Re-Design Graph Neural Networks in Spaces of Continuous Graph Diffusion FunctionalsCode0
SENSEi: Input-Sensitive Compilation for Accelerating GNNs—0
TransERR: Translation-based Knowledge Graph Embedding via Efficient Relation RotationCode1
A Decade of Scholarly Research on Open Knowledge GraphsCode0
TuckerDNCaching: high-quality negative sampling with tucker decompositionCode0
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
Schema First! Learn Versatile Knowledge Graph Embeddings by Capturing Semantics with MASCHInECode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified