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 621–630 of 1192 papers

TitleStatusHype
On Large-scale Evaluation of Embedding Models for Knowledge Graph Completion—0
On Masked Language Models for Contextual Link Prediction—0
On representation power of neural network-based graph embedding and beyond—0
On Self-Distilling Graph Neural Network—0
Curvature Regularization to Prevent Distortion in Graph Embedding—0
On The Expressive Power of Knowledge Graph Embedding Methods—0
Toward Understanding The Effect Of Loss function On Then Performance Of Knowledge Graph Embedding—0
Customized Graph Embedding: Tailoring Embedding Vectors to different Applications—0
Open Knowledge Base Canonicalization with Multi-task Unlearning—0
Open Knowledge Base Canonicalization with Multi-task Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified