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Position Regression On Chili 100K

Métriques

Positional MAE

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle
Positional MAE
Paper TitleRepository
GAT16.336 +/- 0.000CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning-
GraphSAGE16.337 +/- 0.000CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning-
GraphUNet14.824 +/- 0.315CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning-
GIN16.336 +/- 0.000CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning-
EdgeCNN16.336 +/- 0.000CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning-
GCN16.336 +/- 0.000CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning-
Mean16.336CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning-
PMLP16.336 +/- 0.000CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning-
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Position Regression On Chili 100K | SOTA | HyperAI