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 671–680 of 1192 papers

TitleStatusHype
Learning a Distance Metric from a Network—0
A Greedy Bit-flip Training Algorithm for Binarized Knowledge Graph Embeddings—0
Learning Combinatorial Embedding Networks for Deep Graph Matching—0
AGNN: Alternating Graph-Regularized Neural Networks to Alleviate Over-Smoothing—0
Learning Cross-Domain Representation with Multi-Graph Neural Network—0
Learning Embeddings from Knowledge Graphs With Numeric Edge Attributes—0
Learning event representations for temporal segmentation of image sequences by dynamic graph embedding—0
Convolutional Networks on Enhanced Message-Passing Graph Improve Semi-Supervised Classification with Few Labels—0
Controversy Detection: a Text and Graph Neural Network Based Approach—0
Learning Graph Embeddings from WordNet-based Similarity Measures—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified