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 481–490 of 1192 papers

TitleStatusHype
GraphZoom: A multi-level spectral approach for accurate and scalable graph embeddingCode0
SpherE: Expressive and Interpretable Knowledge Graph Embedding for Set RetrievalCode0
DGNN: Decoupled Graph Neural Networks with Structural Consistency between Attribute and Graph Embedding RepresentationsCode0
Balancing Graph Embedding Smoothness in Self-Supervised Learning via Information-Theoretic DecompositionCode0
Graph U-NetsCode0
Balancing between the Local and Global Structures (LGS) in Graph EmbeddingCode0
Development of a Knowledge Graph Embeddings Model for PainCode0
Unify Local and Global Information for Top-N RecommendationCode0
Robust Graph Representation Learning for Local Corruption RecoveryCode0
GraphVAE: Towards Generation of Small Graphs Using Variational AutoencodersCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified