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Graph Sampling

Training GNNs or generating graph embeddings requires graph samples.

Papers

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Showing 81–90 of 101 papers

TitleStatusHype
MD-GCN: A Multi-Scale Temporal Dual Graph Convolution Network for Traffic Flow Prediction—0
Neighborhood Random Walk Graph Sampling for Regularized Bayesian Graph Convolutional Neural Networks—0
Neuro-Symbolic Procedural Planning with Commonsense Prompting—0
Accelerating Graph Sampling for Graph Machine Learning using GPUs—0
Node Copying: A Random Graph Model for Effective Graph Sampling—0
On Random Walk Based Graph Sampling—0
Empirical Risk Minimization and Stochastic Gradient Descent for Relational DataCode0
Hierarchical graph sampling based minibatch learning with chain preservation and variance reductionCode0
Fine-tuning Partition-aware Item Similarities for Efficient and Scalable RecommendationCode0
Class-level Structural Relation Modelling and Smoothing for Visual Representation LearningCode0
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