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
Temporal Graph Networks for Graph Anomaly Detection in Financial Networks—0
Open Knowledge Base Canonicalization with Multi-task Learning—0
TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of ExpertsCode2
TPLLM: A Traffic Prediction Framework Based on Pretrained Large Language Models—0
Applying Self-supervised Learning to Network Intrusion Detection for Network Flows with Graph Neural NetworkCode1
PowerFlowMultiNet: Multigraph Neural Networks for Unbalanced Three-Phase Distribution Systems—0
Negative Sampling in Knowledge Graph Representation Learning: A Review—0
PreRoutGNN for Timing Prediction with Order Preserving Partition: Global Circuit Pre-training, Local Delay Learning and Attentional Cell ModelingCode3
EntailE: Introducing Textual Entailment in Commonsense Knowledge Graph Completion—0
SAGMAN: Stability Analysis of Graph Neural Networks on the Manifolds—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeepGGEntropy Difference0—Unverified