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Graph Sampling

Training GNNs or generating graph embeddings requires graph samples.

Papers

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Showing 1–10 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
Causal structure learning with momentum: Sampling distributions over Markov Equivalence Classes of DAGsCode2
Training Graph Neural Networks with 1000 LayersCode2
Quiver: Supporting GPUs for Low-Latency, High-Throughput GNN Serving with Workload AwarenessCode2
Accelerating Sampling and Aggregation Operations in GNN Frameworks with GPU Initiated Direct Storage AccessesCode1
Generalize a Small Pre-trained Model to Arbitrarily Large TSP InstancesCode1
Accurate, Efficient and Scalable Training of Graph Neural NetworksCode1
Efficient Neural Architecture Search for End-to-end Speech Recognition via Straight-Through GradientsCode1
Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph GenerationCode1
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