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Graph Sampling

Training GNNs or generating graph embeddings requires graph samples.

Papers

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Showing 1–50 of 101 papers

TitleStatusHype
Accelerating Scientific Discovery with Generative Knowledge Extraction, Graph-Based Representation, and Multimodal Intelligent Graph ReasoningCode3
TF-GNN: Graph Neural Networks in TensorFlowCode3
Training Graph Neural Networks with 1000 LayersCode2
Causal structure learning with momentum: Sampling distributions over Markov Equivalence Classes of DAGsCode2
Quiver: Supporting GPUs for Low-Latency, High-Throughput GNN Serving with Workload AwarenessCode2
Efficient Graph Deep Learning in TensorFlow with tf_geometricCode1
Heterogeneous Graph TransformerCode1
Retrofitting Temporal Graph Neural Networks with TransformerCode1
Accurate, Efficient and Scalable Training of Graph Neural NetworksCode1
Graph Sampling-based Meta-Learning for Molecular Property PredictionCode1
Scalable Graph Neural Networks via Bidirectional PropagationCode1
Rethinking Explaining Graph Neural Networks via Non-parametric Subgraph MatchingCode1
GIST: Distributed Training for Large-Scale Graph Convolutional NetworksCode1
Efficient Neural Architecture Search for End-to-end Speech Recognition via Straight-Through GradientsCode1
SIGN: Scalable Inception Graph Neural NetworksCode1
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate CommunicationCode1
Neighborhood Matching Network for Entity AlignmentCode1
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNsCode1
GraphSAINT: Graph Sampling Based Inductive Learning MethodCode1
Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph GenerationCode1
Generalize a Small Pre-trained Model to Arbitrarily Large TSP InstancesCode1
GRAPES: Learning to Sample Graphs for Scalable Graph Neural NetworksCode1
HyFactor: Hydrogen-count labelled graph-based defactorization AutoencoderCode1
Accelerating Sampling and Aggregation Operations in GNN Frameworks with GPU Initiated Direct Storage AccessesCode1
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs—0
Efficient Directed Graph Sampling via Gershgorin Disc Alignment—0
Bearing Fault Diagnosis using Graph Sampling and Aggregation Network—0
Adaptive Least Mean Squares Estimation of Graph Signals—0
Graph sampling with determinantal processes—0
Edge Sampling of Graphs: Graph Signal Processing Approach With Edge Smoothness—0
Dynamic Sensor Placement Based on Sampling Theory for Graph Signals—0
Bayesian structure learning and sampling of Bayesian networks with the R package BiDAG—0
Distributed Graph Neural Network Inference With Just-In-Time Compilation For Industry-Scale Graphs—0
GraphBGS: Background Subtraction via Recovery of Graph Signals—0
DiskGNN: Bridging I/O Efficiency and Model Accuracy for Out-of-Core GNN Training—0
Graph Sampling for Scalable and Expressive Graph Neural Networks on Homophilic Graphs—0
Counting Motifs with Graph Sampling—0
GLISP: A Scalable GNN Learning System by Exploiting Inherent Structural Properties of Graphs—0
A Sampling Theory Perspective of Graph-based Semi-supervised Learning—0
GDM: Dual Mixup for Graph Classification with Limited Supervision—0
GCM-Net: Graph-enhanced Cross-Modal Infusion with a Metaheuristic-Driven Network for Video Sentiment and Emotion Analysis—0
Graph Sampling Based Deep Metric Learning for Generalizable Person Re-Identification—0
Graph Sampling for Matrix Completion Using Recurrent Gershgorin Disc Shift—0
Gophormer: Ego-Graph Transformer for Node Classification—0
Folded Graph Signals: Sensing with Unlimited Dynamic Range—0
GraphSOS: Graph Sampling and Order Selection to Help LLMs Understand Graphs Better—0
FedGraph: Federated Graph Learning with Intelligent Sampling—0
Classification of developmental and brain disorders via graph convolutional aggregation—0
Federated Graph Learning with Adaptive Importance-based Sampling—0
Fast Graph Sampling for Short Video Summarization using Gershgorin Disc Alignment—0
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