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Graph Sampling

Training GNNs or generating graph embeddings requires graph samples.

Papers

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Showing 51–100 of 101 papers

TitleStatusHype
Simple yet Effective Graph Distillation via Clustering—0
STGIN: Spatial-Temporal Graph Interaction Network for Large-scale POI Recommendation—0
SynGraphy: Succinct Summarisation of Large Networks via Small Synthetic Representative Graphs—0
Text Graph Transformer for Document Classification—0
The Limits of Graph Samplers for Training Inductive Recommender Systems: Extended results—0
Towards joint graph learning and sampling set selection from data—0
Unsupervised Learning of Morphology with Graph Sampling—0
Unveiling Privacy Vulnerabilities: Investigating the Role of Structure in Graph Data—0
Adaptive Graph Signal Processing: Algorithms and Optimal Sampling Strategies—0
Adaptive Least Mean Squares Estimation of Graph Signals—0
A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs—0
A Sampling Theory Perspective of Graph-based Semi-supervised Learning—0
Bayesian structure learning and sampling of Bayesian networks with the R package BiDAG—0
Bearing Fault Diagnosis using Graph Sampling and Aggregation Network—0
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs—0
BMG-Q: Localized Bipartite Match Graph Attention Q-Learning for Ride-Pooling Order Dispatch—0
Classification of developmental and brain disorders via graph convolutional aggregation—0
Counting Motifs with Graph Sampling—0
DiskGNN: Bridging I/O Efficiency and Model Accuracy for Out-of-Core GNN Training—0
Distributed Graph Neural Network Inference With Just-In-Time Compilation For Industry-Scale Graphs—0
Dynamic Sensor Placement Based on Sampling Theory for Graph Signals—0
Edge Sampling of Graphs: Graph Signal Processing Approach With Edge Smoothness—0
Efficient Directed Graph Sampling via Gershgorin Disc Alignment—0
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
GLISP: A Scalable GNN Learning System by Exploiting Inherent Structural Properties of Graphs—0
Gophormer: Ego-Graph Transformer for Node Classification—0
GraphSOS: Graph Sampling and Order Selection to Help LLMs Understand Graphs Better—0
GraphBGS: Background Subtraction via Recovery of Graph Signals—0
Graph Neural Network for Stress Predictions in Stiffened Panels Under Uniform Loading—0
Graph Sampling for Matrix Completion Using Recurrent Gershgorin Disc Shift—0
Graph sampling for node embedding—0
Graph Sampling for Scalable and Expressive Graph Neural Networks on Homophilic Graphs—0
Graph sampling with determinantal processes—0
Impression-Informed Multi-Behavior Recommender System: A Hierarchical Graph Attention Approach—0
Interpretable A-posteriori Error Indication for Graph Neural Network Surrogate Models—0
Keyed Chaotic Dynamics for Privacy-Preserving Neural Inference—0
Learning Large-scale Network Embedding from Representative Subgraph—0
Learning Parameters for Balanced Index Influence Maximization—0
Light-weight End-to-End Graph Interest Network for CTR Prediction in E-commerce Search—0
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
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