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Datasets/QM9

QM9

QM9 provides quantum chemical properties (at DFT level) for a relevant, consistent, and comprehensive chemical space of small organic molecules. This database may serve the benchmarking of existing methods, development of new methods, such as hybrid quantum mechanics/machine learning, and systematic identification of structure-property relationships.

Source: QM9 Dataset Image Source: https://pubs.acs.org/doi/pdf/10.1021/ci300415d

Benchmarks

Atomistic Description/MAEAtomistic Description/avg. log MAEDrug Discovery/Error ratioFormation Energy/MAEGraph Property Prediction/Standardized MAEGraph Property Prediction/logMAEGraph Property Prediction/alpha (ma)Graph Property Prediction/gap (meV)Graph Regression/Inference Time (ms)Molecular Property Prediction/MAEMolecular Property Prediction/avg. log MAEMulti-Task Learning/∆m%Prediction/Edit DistanceTransfer Learning/∆m%Unconditional Molecule Generation/ValidityUnconditional Molecule Generation/PoseBusters Internal Energy

Related Benchmarks

QM9: UATOM/Graph Regression/MAEQM9: ZPVE/Graph Regression/MAEQM9: del e/Graph Regression/MAEQM9: mu/Graph Regression/MAE

Statistics

Papers
76
Benchmarks
16

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Tasks

Atomistic DescriptionDrug DiscoveryFormation EnergyGraph Property PredictionGraph RegressionMolecular Graph GenerationMolecular Property PredictionMulti-Task LearningNMR J-couplingPredictionTime SeriesTransfer LearningUnconditional Molecule Generation