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 931–940 of 1192 papers

TitleStatusHype
Toward Understanding The Effect of Loss Function on The Performance of Knowledge Graph Embedding—0
Knowledge Graph Embedding: A Probabilistic Perspective and Generalization Bounds—0
Graph Neural Networks For Multi-Image Matching—0
Iterative Deep Graph Learning for Graph Neural Networks—0
Global graph curvature—0
Unsupervised Universal Self-Attention Network for Graph Classification—0
NoiGAN: NOISE AWARE KNOWLEDGE GRAPH EMBEDDING WITH GAN—0
PINE: Universal Deep Embedding for Graph Nodes via Partial Permutation Invariant Set Functions—0
Learning Universal Graph Neural Network Embeddings With Aid Of Transfer LearningCode0
Triplet-Aware Scene Graph Embeddings—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified