Open Graph Benchmark (OGB)
Emerging7papers using it
2021first seen
The Open Graph Benchmark (OGB) is a collection of large-scale node classification datasets used to evaluate the performance of graph neural networks (GNNs).
Papers using Open Graph Benchmark (OGB) (7)
- gHAWK: Local and Global Structure Encoding for Scalable Training of Graph Neural Networks on Knowledge GraphsEnhanced Soups for Graph Neural NetworksPROXI: Challenging the GNNs for Link PredictionNeo-GNNs: Neighborhood Overlap-aware Graph Neural Networks for Link
PredictionBag of Tricks for Node Classification with Graph Neural NetworksResidual Network and Embedding Usage: New Tricks of Node Classification
with Graph Convolutional NetworksSeq-HGNN: Learning Sequential Node Representation on Heterogeneous Graph