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Graph Sampling

Training GNNs or generating graph embeddings requires graph samples.

Papers

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Showing 51–60 of 101 papers

TitleStatusHype
Efficient Signed Graph Sampling via Balancing & Gershgorin Disc Perfect Alignment—0
Evaluating Graph Signal Processing for Neuroimaging Through Classification and Dimensionality Reduction—0
Fast Graph Sampling for Short Video Summarization using Gershgorin Disc Alignment—0
Federated Graph Learning with Adaptive Importance-based Sampling—0
FedGraph: Federated Graph Learning with Intelligent Sampling—0
Folded Graph Signals: Sensing with Unlimited Dynamic Range—0
GCM-Net: Graph-enhanced Cross-Modal Infusion with a Metaheuristic-Driven Network for Video Sentiment and Emotion Analysis—0
GDM: Dual Mixup for Graph Classification with Limited Supervision—0
Physics-Guided Fair Graph Sampling for Water Temperature Prediction in River Networks—0
Point Cloud Sampling via Graph Balancing and Gershgorin Disc Alignment—0
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