Web1. Large scale. The OGB datasets are orders-of-magnitude larger than existing benchmarks and can be categorized into three different scales (small, medium, and large). Even the “small” OGB graphs have more than 100 thousand nodes or more than 1 million edges, but are small enough to Here we propose a large-scale graph ML competition, OGB Large-Scale Challenge (OGB-LSC), to encourage the development of state-of-the-art graph ML models for massive modern datasets. Specifically, we present three datasets: MAG240M, WikiKG90M, and PCQM4M, that are unprecedentedly large in scale … Ver mais Machine Learning (ML) on graphs has attracted immense attention in recent years because of the prevalence of graph-structured data in real-world applications. Modern application domains include web-scale social networks, … Ver mais Details about our datasets and our initial baseline analysis are described in our OGB-LSC paper.If you use OGB-LSC in your work, please cite … Ver mais The OGB-LSC team can be reached at [email protected]. For discussion or general questions about the datasets, use our Github … Ver mais

KDD 2024 Celebrates Winning Teams of 25th Annual KDD Cup

WebOpen Graph Benchmark: Large-Scale Challenge Stanford, USA Invited Talk at Stanford Graph Learning Workshop September 16, 2024 Open Graph Benchmark: Large-Scale Challenge Virtual, Japan Invited Seminar Talk at RIKEN AIP Center September 2, 2024 Advances in GNNs: Expressive Power, Pre-training, and OGB KDD births deaths and marriages sunshine coast

Do Transformers Really Perform Bad for Graph Representation?

Webrealistic and large-scale graph datasets, exploring the potential of expressive models for big graphs. Here we present a large-scale graph ML challenge, OGB Large-Scale Challenge (OGB-LSC), to facilitate the development of state-of-the-art graph ML models … WebIn order to advance large-scale graph machine learning, the Open Graph Benchmark Large Scale Challenge (OGB-LSC) was proposed at the KDD Cup 2024. The PCQM4M-LSC dataset defines a molecular HOMO-LUMO property prediction task on about 3.8M graphs. In this short paper, we show our current work-in-progress solution which builds … WebLearn about MAG240M-LSC and Python package Dataset: Learn about the dataset and the prediction task. Python package tutorial Dataset object: Learn about how to prepare and use the dataset with our package. Performance evaluator: Learn about how to evaluate … births deaths and marriages search