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 961–970 of 1192 papers

TitleStatusHype
Invariant embedding for graph classification—0
Temporal Analysis of Reddit Networks via Role Embeddings—0
CensNet: Convolution with Edge-Node Switching in Graph Neural Networks—0
Graph Embedding Using Infomax for ASD Classification and Brain Functional Difference Detection—0
Graph Node Embeddings using Domain-Aware Biased Random Walks—0
A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding ModelsCode0
Authorship Recognition with Short-Text using Graph-based Techniques—0
Tripartite Heterogeneous Graph Propagation for Large-scale Social Recommendation—0
Hyperlink Regression via Bregman Divergence—0
Improving Skip-Gram based Graph Embeddings via Centrality-Weighted Sampling—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified