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Graph Sampling

Training GNNs or generating graph embeddings requires graph samples.

Papers

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Showing 61–70 of 101 papers

TitleStatusHype
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
Training Graph Neural Networks with 1000 LayersCode2
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
GIST: Distributed Training for Large-Scale Graph Convolutional NetworksCode1
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