The Open Graph Benchmark (OGB) is a collection of realistic, large-scale, and diverse benchmark datasets for machine learning on graphs. OGB datasets are automatically …

The Open Graph Benchmark (OGB) is a collection of benchmark datasets, data loaders, and evaluators for graph machine learning. Datasets cover a variety of graph machine learning …

OGB contains graph datasets that are managed by data loaders. The loaders handle downloading and pre-processing of the datasets. Additionally, OGB has standardized evaluators and …

OGB提供了一个自动的端到端图学习管道，该管道简化并标准化了图数据加载、实验设置和模型评估的过程。OGB可以自动化数据集处理和拆分， 并且与Pytorch、 Pytorch Geometic (PyG) …

2022年10月20日 · Open Graph Benchmark (OGB) 是一个图 深度学习 的基准数据集。 Open Graph Benchmark: Datasets for Machine Learning on Graphs. 那么其包含了哪些数据集呢？ …

2020年5月2日 · Abstract: We present the Open Graph Benchmark (OGB), a diverse set of challenging and realistic benchmark datasets to facilitate scalable, robust, and reproducible …

2024年11月29日 · Open Graph Benchmark (OGB) 是由斯坦福大学 SNAP (Stanford Network Analysis Platform) 团队开发的一个图机器学习基准数据集集合。 这个项目提供了多种图机器学 …

We highlight two key features of OGB, namely, (1) easy-to-use data loaders, and (2) standardized evaluators. We prepare easy-to-use PyTorch Geometric and DGL data loaders. We handle …

We present the OPEN GRAPH BENCHMARK (OGB), a diverse set of challenging and realistic benchmark datasets to facilitate scalable, robust, and reproducible graph machine learning …

The Open Graph Benchmark (OGB) is a collection of realistic, large-scale, and diverse benchmark datasets for machine learning on graphs. OGB datasets are automatically …