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 1081–1090 of 1192 papers

TitleStatusHype
DualDE: Dually Distilling Knowledge Graph Embedding for Faster and Cheaper Reasoning—0
Disentangling Interpretable Generative Parameters of Random and Real-World Graphs—0
Semisupervised regression in latent structure networks on unknown manifolds—0
GARNET: A Spectral Approach to Robust and Scalable Graph Neural Networks—0
AN-GCN: An Anonymous Graph Convolutional Network Defense Against Edge-Perturbing Attack—0
GB-RVFL: Fusion of Randomized Neural Network and Granular Ball Computing—0
DisenE: Disentangling Knowledge Graph Embeddings—0
Sequence-to-Sequence Knowledge Graph Completion and Question Answering—0
GEFF: Graph Embedding for Functional Fingerprinting—0
Generalizable Cross-Graph Embedding for GNN-based Congestion Prediction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified