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 601–610 of 1192 papers

TitleStatusHype
Cross-Modality Attention with Semantic Graph Embedding for Multi-Label Classification—0
NASGEM: Neural Architecture Search via Graph Embedding Method—0
Negative Sampling in Knowledge Graph Representation Learning: A Review—0
Cross-validation of matching correlation analysis by resampling matching weights—0
Neighbor2vec: an efficient and effective method for Graph Embedding—0
Scalable Hypergraph Embedding System—0
Cross Version Defect Prediction with Class Dependency Embeddings—0
Network representation learning systematic review: ancestors and current development state—0
CS-MLGCN : Multiplex Graph Convolutional Networks for Community Search in Multiplex Networks—0
Neural Networks in a Product of Hyperbolic Spaces—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified