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 181–190 of 1192 papers

TitleStatusHype
Rule-Guided Joint Embedding Learning over Knowledge Graphs—0
VEXIR2Vec: An Architecture-Neutral Embedding Framework for Binary SimilarityCode2
FoldExplorer: Fast and Accurate Protein Structure Search with Sequence-Enhanced Graph Embedding—0
Improving embedding of graphs with missing data by soft manifolds—0
Stockformer: A Price-Volume Factor Stock Selection Model Based on Wavelet Transform and Multi-Task Self-Attention NetworksCode1
Two Stream Scene Understanding on Graph Embedding—0
HKTGNN: Hierarchical Knowledge Transferable Graph Neural Network-based Supply Chain Risk Assessment—0
Visualizing DNA reaction trajectories with deep graph embedding approachesCode0
Pointer Networks with Q-Learning for Combinatorial Optimization—0
Contrastive Deep Nonnegative Matrix Factorization for Community DetectionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified