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 81–90 of 1192 papers

TitleStatusHype
Cloudy with a Chance of Anomalies: Dynamic Graph Neural Network for Early Detection of Cloud Services' User AnomaliesCode0
GRVFL-MV: Graph Random Vector Functional Link Based on Multi-View Learning—0
The Role of Graph Topology in the Performance of Biomedical Knowledge Graph Completion ModelsCode0
A Survey on Signed Graph Embedding: Methods and Applications—0
CL4KGE: A Curriculum Learning Method for Knowledge Graph Embedding—0
GSIFN: A Graph-Structured and Interlaced-Masked Multimodal Transformer-based Fusion Network for Multimodal Sentiment AnalysisCode0
Single-cell Curriculum Learning-based Deep Graph Embedding ClusteringCode0
Predictive Multiplicity of Knowledge Graph Embeddings in Link Prediction—0
Conformalized Answer Set Prediction for Knowledge Graph Embedding—0
Concept Graph Embedding Models for Enhanced Accuracy and InterpretabilityCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified