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Long Range Graph Benchmark (LRGB)

홈페이지 · 논문 76편

The Long Range Graph Benchmark (LRGB) is a collection of 5 graph learning datasets that arguably require long-range reasoning to achieve strong performance in a given task. The 5 datasets in this benchmark can be used to prototype new models that can capture long range dependencies in graphs. | Dataset | Domain | Task | |---|---|---| | PascalVOC-SP| Computer Vision | Node Classification | | COCO-SP | Computer Vision | Node Classification | | PCQM-Contact | Quantum Chemistry | Link Prediction | | Peptides-func | Chemistry | Graph Classification | | Peptides-struct | Chemistry | Graph Regression |

Graphs

벤치마크

Graph Classification on Peptides-func 결과 88개
Graph Regression on Peptides-struct 결과 39개
Node Classification on PascalVOC-SP 결과 21개
Node Classification on COCO-SP 결과 19개
Link Prediction on PCQM-Contact 결과 18개