SOTAVerified

Graph Embedding

Graph embeddings learn a mapping from a network to a vector space, while preserving relevant network properties.

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Papers

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Showing 141–150 of 1192 papers

TitleStatusHype
Graph Neural Networks for Distributed Power Allocation in Wireless Networks: Aggregation Over-the-AirCode1
Distributed-Memory Sparse Kernels for Machine LearningCode1
Adversarial Directed Graph EmbeddingCode1
Expressive Power of Invariant and Equivariant Graph Neural NetworksCode1
Embedding API Dependency Graph for Neural Code GenerationCode1
Bipartite Graph Embedding via Mutual Information MaximizationCode1
Adversarial Graph Embeddings for Fair Influence Maximization over Social NetworksCode1
Evaluating Node Embeddings of Complex NetworksCode1
An Unsupervised Framework for Comparing Graph EmbeddingsCode1
AutoSF: Searching Scoring Functions for Knowledge Graph EmbeddingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified