Open Graph Benchmark (OGB)
收藏arXiv2021-02-25 更新2024-07-30 收录
下载链接：
https://ogb.stanford.edu
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资源简介：
Open Graph Benchmark (OGB) 是一个多样化的挑战性实际基准数据集，旨在促进图机器学习（ML）研究的规模化、鲁棒性和可重复性。OGB 数据集规模大，涵盖多个重要的图 ML 任务，并覆盖从社交和信息网络到生物网络、分子图、源代码 AST 和知识图谱等多个领域。
Open Graph Benchmark (OGB) is a diverse and challenging real-world benchmark dataset designed to advance the scalability, robustness, and reproducibility of graph machine learning (ML) research. The OGB dataset has a large scale, encompasses a range of critical graph ML tasks, and spans multiple domains ranging from social and information networks, biological networks, molecular graphs, abstract syntax trees (ASTs) of source code, to knowledge graphs.
创建时间：
2020-05-02
