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 481–490 of 1192 papers

TitleStatusHype
CS-TGN: Community Search via Temporal Graph Neural NetworksCode0
Multi-modal Multi-kernel Graph Learning for Autism Prediction and Biomarker Discovery—0
Diversity matters: Robustness of bias measurements in WikidataCode0
A parameter-free graph reduction for spectral clustering and SpectralNetCode0
Random projection tree similarity metric for SpectralNetCode0
Multi-Paradigm Analysis of Thai Capital Market Linkages: Bivariate/Vine Copulas, Granger Causality, Network Centrality, and Graph Neural Network/Graph Embedding ApproachesCode0
Random Projection Forest Initialization for Graph Convolutional NetworksCode0
Graph Construction using Principal Axis Trees for Simple Graph ConvolutionCode0
Refining a k-nearest neighbor graph for a computationally efficient spectral clusteringCode0
Approximate spectral clustering with eigenvector selection and self-tuned kCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified