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 101–110 of 1192 papers

TitleStatusHype
Unified Interpretation of Smoothing Methods for Negative Sampling Loss Functions in Knowledge Graph EmbeddingCode0
Croppable Knowledge Graph Embedding—0
Spectral Graph Reasoning Network for Hyperspectral Image Classification—0
Empowering Interdisciplinary Insights with Dynamic Graph Embedding Trajectories—0
Light-weight End-to-End Graph Interest Network for CTR Prediction in E-commerce Search—0
Toward Structure Fairness in Dynamic Graph Embedding: A Trend-aware Dual Debiasing ApproachCode0
Communication-Efficient Federated Knowledge Graph Embedding with Entity-Wise Top-K Sparsification—0
Personalized Federated Knowledge Graph Embedding with Client-Wise Relation Graph—0
UniGLM: Training One Unified Language Model for Text-Attributed Graph EmbeddingCode1
Algorithm Selection for Optimal Multi-Agent Path Finding via Graph Embedding—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified