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 151–160 of 1192 papers

TitleStatusHype
Graph Convolutional Subspace Clustering: A Robust Subspace Clustering Framework for Hyperspectral ImageCode1
Brain Graph Super-Resolution Using Adversarial Graph Neural Network with Application to Functional Brain ConnectivityCode1
One-Hot Graph Encoder EmbeddingCode1
Accurate Learning of Graph Representations with Graph Multiset PoolingCode1
Adversarially Regularized Graph Autoencoder for Graph EmbeddingCode1
Composition-based Multi-Relational Graph Convolutional NetworksCode1
CAKE: A Scalable Commonsense-Aware Framework For Multi-View Knowledge Graph CompletionCode1
Highly Efficient Knowledge Graph Embedding Learning with Orthogonal Procrustes AnalysisCode1
Can We Predict New Facts with Open Knowledge Graph Embeddings? A Benchmark for Open Link PredictionCode1
AutoSF: Searching Scoring Functions for Knowledge Graph EmbeddingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified