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 1031–1040 of 1192 papers

TitleStatusHype
Dynamic Joint Variational Graph Autoencoders—0
Exploiting Network Structures to Improve Semantic Representation for the Financial Domain—0
Exploring Graph Mamba: A Comprehensive Survey on State-Space Models for Graph Learning—0
Dynamic Graph Embedding via LSTM History Tracking—0
Self-Supervised Graph Embedding Clustering—0
Semantically Enhanced Models for Commonsense Knowledge Acquisition—0
Exponential Family Graph Embeddings—0
A parameterised model for link prediction using node centrality and similarity measure based on graph embedding—0
EXTRACT: Explainable Transparent Control of Bias in Embeddings—0
Extracting Attentive Social Temporal Excitation for Sequential Recommendation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified