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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
Quiver: Supporting GPUs for Low-Latency, High-Throughput GNN Serving with Workload AwarenessCode2
Causal structure learning with momentum: Sampling distributions over Markov Equivalence Classes of DAGsCode2
Training Graph Neural Networks with 1000 LayersCode2
Efficient Graph Deep Learning in TensorFlow with tf_geometricCode1
HyFactor: Hydrogen-count labelled graph-based defactorization AutoencoderCode1
Efficient Neural Architecture Search for End-to-end Speech Recognition via Straight-Through GradientsCode1
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNsCode1
GIST: Distributed Training for Large-Scale Graph Convolutional NetworksCode1
Generalize a Small Pre-trained Model to Arbitrarily Large TSP InstancesCode1
GraphSAINT: Graph Sampling Based Inductive Learning MethodCode1
Accelerating Sampling and Aggregation Operations in GNN Frameworks with GPU Initiated Direct Storage AccessesCode1
Heterogeneous Graph TransformerCode1
Rethinking Explaining Graph Neural Networks via Non-parametric Subgraph MatchingCode1
Neighborhood Matching Network for Entity AlignmentCode1
Scalable Graph Neural Networks via Bidirectional PropagationCode1
Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate CommunicationCode1
Retrofitting Temporal Graph Neural Networks with TransformerCode1
Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph GenerationCode1
Graph Sampling-based Meta-Learning for Molecular Property PredictionCode1
Accurate, Efficient and Scalable Training of Graph Neural NetworksCode1
GRAPES: Learning to Sample Graphs for Scalable Graph Neural NetworksCode1
SIGN: Scalable Inception Graph Neural NetworksCode1
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
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 with determinantal processes—0
Counting Motifs with Graph Sampling—0
A Sampling Theory Perspective of Graph-based Semi-supervised Learning—0
Graph Sampling for Matrix Completion Using Recurrent Gershgorin Disc Shift—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 for node embedding—0
Folded Graph Signals: Sensing with Unlimited Dynamic Range—0
GLISP: A Scalable GNN Learning System by Exploiting Inherent Structural Properties of Graphs—0
Gophormer: Ego-Graph Transformer for Node Classification—0
FedGraph: Federated Graph Learning with Intelligent Sampling—0
GraphSOS: Graph Sampling and Order Selection to Help LLMs Understand Graphs Better—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
A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs—0
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