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 1061–1070 of 1192 papers

TitleStatusHype
Dimensionality Reduction of Hyperspectral Imagery Based on Spatial-spectral Manifold Learning—0
Dynamic Graph Representation Learning via Self-Attention NetworksCode0
Attentional Heterogeneous Graph Neural Network: Application to Program Reidentification—0
Improved Knowledge Graph Embedding using Background Taxonomic Information—0
dynnode2vec: Scalable Dynamic Network Embedding—0
Spatio-Temporal Action Graph NetworksCode0
From Node Embedding to Graph Embedding: Scalable Global Graph Kernel via Random Features—0
DynamicGEM: A Library for Dynamic Graph Embedding MethodsCode0
TGE-viz : Transition Graph Embedding for Visualization of Plan Traces and Domains—0
MGCN: Semi-supervised Classification in Multi-layer Graphs with Graph Convolutional NetworksCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified