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 881–890 of 1192 papers

TitleStatusHype
What the Vec? Towards Probabilistically Grounded Embeddings—0
When Radiology Report Generation Meets Knowledge Graph—0
DyGCN: Dynamic Graph Embedding with Graph Convolutional Network—0
Whom to Learn From? Graph- vs. Text-based Word Embeddings—0
Why does Negative Sampling not Work Well? Analysis of Convexity in Negative Sampling—0
Zero-Shot Medical Information Retrieval via Knowledge Graph Embedding—0
Neural IR Meets Graph Embedding: A Ranking Model for Product Search—0
A Relational Tucker Decomposition for Multi-Relational Link Prediction—0
Dynamic Graph Embedding via LSTM History Tracking—0
Dynamic Joint Variational Graph Autoencoders—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified