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 441–450 of 1192 papers

TitleStatusHype
Fast Knowledge Graph Completion using Graphics Processing Units—0
Graph Embedded Intuitionistic Fuzzy Random Vector Functional Link Neural Network for Class Imbalance LearningCode0
GRAN is superior to GraphRNN: node orderings, kernel- and graph embeddings-based metrics for graph generatorsCode0
Improving Heterogeneous Graph Learning with Weighted Mixed-Curvature Product ManifoldCode0
Source-Aware Embedding Training on Heterogeneous Information Networks—0
TransformerG2G: Adaptive time-stepping for learning temporal graph embeddings using transformersCode0
Re-Think and Re-Design Graph Neural Networks in Spaces of Continuous Graph Diffusion FunctionalsCode0
SENSEi: Input-Sensitive Compilation for Accelerating GNNs—0
A Decade of Scholarly Research on Open Knowledge GraphsCode0
Transforming Graphs for Enhanced Attribute Clustering: An Innovative Graph Transformer-Based Method—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified