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Graph Sampling

Training GNNs or generating graph embeddings requires graph samples.

Papers

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Showing 71–80 of 101 papers

TitleStatusHype
FedGraph: Federated Graph Learning with Intelligent Sampling—0
Gophormer: Ego-Graph Transformer for Node Classification—0
Fast Graph Sampling for Short Video Summarization using Gershgorin Disc Alignment—0
Scaffold-Induced Molecular Graph (SIMG): Effective Graph Sampling Methods for High-Throughput Computational Drug Discovery—0
Are Negative Samples Necessary in Entity Alignment? An Approach with High Performance, Scalability and RobustnessCode0
Bayesian structure learning and sampling of Bayesian networks with the R package BiDAG—0
Graph Sampling Based Deep Metric Learning for Generalizable Person Re-IdentificationCode0
Point Cloud Sampling via Graph Balancing and Gershgorin Disc Alignment—0
Pre-Training on Dynamic Graph Neural NetworksCode0
Learning Parameters for Balanced Index Influence Maximization—0
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