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 331–340 of 1192 papers

TitleStatusHype
Generating Post-hoc Explanations for Skip-gram-based Node Embeddings by Identifying Important Nodes with Bridgeness—0
Combining Contrastive Learning and Knowledge Graph Embeddings to develop medical word embeddings for the Italian language—0
A Comprehensive Survey on Deep Graph Representation Learning—0
A Greedy Bit-flip Training Algorithm for Binarized Knowledge Graph Embeddings—0
GenURL: A General Framework for Unsupervised Representation Learning—0
AGNN: Alternating Graph-Regularized Neural Networks to Alleviate Over-Smoothing—0
Co-embedding of Nodes and Edges with Graph Neural Networks—0
Generalized Graph Embedding Models—0
Coarse-to-Fine Classification via Parametric and Nonparametric Models for Computer-Aided Diagnosis—0
A Relational Tucker Decomposition for Multi-Relational Link Prediction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified