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Graph Sampling

Training GNNs or generating graph embeddings requires graph samples.

Papers

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Showing 26–50 of 101 papers

TitleStatusHype
Interpretable A-posteriori Error Indication for Graph Neural Network Surrogate Models—0
Classification of developmental and brain disorders via graph convolutional aggregation—0
Cooperative Minibatching in Graph Neural NetworksCode0
Causal structure learning with momentum: Sampling distributions over Markov Equivalence Classes of DAGsCode2
GRAPES: Learning to Sample Graphs for Scalable Graph Neural NetworksCode1
Graph Neural Network for Stress Predictions in Stiffened Panels Under Uniform Loading—0
GDM: Dual Mixup for Graph Classification with Limited Supervision—0
Impression-Informed Multi-Behavior Recommender System: A Hierarchical Graph Attention Approach—0
STGIN: Spatial-Temporal Graph Interaction Network for Large-scale POI Recommendation—0
A Topology-aware Analysis of Graph Collaborative FilteringCode0
Class-level Structural Relation Modelling and Smoothing for Visual Representation LearningCode0
Graph Sampling-based Meta-Learning for Molecular Property PredictionCode1
Accelerating Sampling and Aggregation Operations in GNN Frameworks with GPU Initiated Direct Storage AccessesCode1
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate CommunicationCode1
Quiver: Supporting GPUs for Low-Latency, High-Throughput GNN Serving with Workload AwarenessCode2
SynGraphy: Succinct Summarisation of Large Networks via Small Synthetic Representative Graphs—0
MD-GCN: A Multi-Scale Temporal Dual Graph Convolution Network for Traffic Flow Prediction—0
Rethinking Explaining Graph Neural Networks via Non-parametric Subgraph MatchingCode1
Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph GenerationCode1
Dynamic Sensor Placement Based on Sampling Theory for Graph Signals—0
Characterizing the Efficiency of Graph Neural Network Frameworks with a Magnifying GlassCode0
Efficient Directed Graph Sampling via Gershgorin Disc Alignment—0
Graph sampling for node embedding—0
Joint Network Topology Inference via a Shared Graphon ModelCode0
Sampling for network function learning—0
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