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18.08.2021 · unread, New OGB-LSC datasets and public leaderboards released. Hi everyone, We are excited to release OGB package v1.3.2, where you can use the new OGB-LSC datasets. Sep 29. . Open Graph Benchmark. Aug 18. OGB-LSC dataset updates. Hi OGB-LSC participants, Thank you all again for participating in the OGB-LSC at the KDD Cup 2021.

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

Open Graph Benchmark: Datasets for Machine Learning on Graphs Weihua Hu1, Matthias Fey2, Marinka Zitnik3, Yuxiao Dong4, Hongyu Ren 1, Bowen Liu5, Michele Catasta , Jure Leskovec1 1Department of Computer Science, 5Chemistry, Stanford University 2Department of Computer Science, TU Dortmund University 3Department of Biomedical Informatics, Harvard University …

least, benchmarks need to provide different types of tasks, such as node classification, link prediction, and graph classification. Present work: OGB. Here, we present the OPEN GRAPH BENCHMARK (OGB) with the goal of facilitating scalable, robust, and reproducible graph ML research. The premise of OGB is to

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 downloaded, processed, and split using the OGB Data Loader. The model performance can be evaluated using the OGB Evaluator in a unified manner.

OGB datasets are large-scale, encompass multiple important graph ML tasks, and cover a diverse range of domains, ranging from social and information networks to ...

The Open Graph Benchmark - Large Scale Challenge (OGB-LSC) is a set of three large real-world datasets (between 55M and 1.7B edges) focusing on three ...

28 rader · 12 code implementations in PyTorch. We present the Open Graph Benchmark (OGB), …

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 (ML) research. OGB datasets are large-scale, encompass multiple important graph ML tasks, and cover a diverse range of domains, ranging from social and information ...

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

47 rader · Horace He (Cornell) Paper, Code. 96,247. GeForce RTX 2080 (11GB GPU) Oct 27, …

02.05.2020 · 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 (ML) research. OGB datasets are large-scale, encompass multiple important graph ML tasks and cover a diverse range of domains, ranging from social and information networks to …

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 downloaded, processed, and split using the OGB Data Loader.The model performance can be evaluated using the OGB Evaluator in a unified manner. OGB is a community-driven initiative in active …

We present the Open Graph Benchmark (OGB), a diverse set of challenging and ... OGB datasets are large-scale, encompass multiple important graph ML tasks ...

We present the Open Graph Benchmark (OGB), a diverse set of challenging and realistic benchmark datasets to facilitate scalable, robust, and reproducible ...

Open Graph Benchmark §Many methods have been developed. §Over 300 leaderboard submissions §Drastic accuracy improvementon many datasets Weihua Hu, Stanford University 11 Source: Papers with code ogbg-molpcba(molecule classification) ogbn-products (product classification) +4% AP improvement over our best baseline +5% accuracy improvement

May 02, 2020 · 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 (ML) research. OGB datasets are large-scale, encompass multiple important graph ML tasks and cover a diverse range of domains, ranging from social and information networks to biological networks, molecular graphs, and ...

Aug 18, 2021 · Initial test submission deadline in one day. Hi OGB-LSC participants, This is a reminder that the initial test submission ends in about one day: May 10. . Open Graph Benchmark. May 1. [OGB-LSC @ KDD Cup 2021] Initial test submission by May 10th.

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