Quantum Machine (QM) datasets
GPTKB entity
Statements (31)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
scientific dataset collection
|
| gptkbp:citation |
Faber, F. A., et al. (2017). Prediction errors of molecular machine learning models lower than hybrid DFT error. J. Chem. Theory Comput.
Ramakrishnan, R., et al. (2014). Quantum chemistry structures and properties of 134 kilo molecules. Scientific Data. Ramakrishnan, R., et al. (2015). Electronic spectra from TDDFT and machine learning in chemical space. J. Chem. Phys. |
| gptkbp:contains |
molecular properties
quantum mechanical calculations |
| gptkbp:creator |
Quantum Machine group
|
| gptkbp:field |
gptkb:machine_learning
quantum chemistry |
| gptkbp:format |
.csv
.hdf5 .xyz |
| https://www.w3.org/2000/01/rdf-schema#label |
Quantum Machine (QM) datasets
|
| gptkbp:license |
varies by dataset
|
| gptkbp:trainer |
gptkb:QM7b
gptkb:QM9 gptkb:QM7 gptkb:QM8 QMugs |
| gptkbp:type |
forces
energies molecular structures HOMO/LUMO energies dipole moments polarizabilities |
| gptkbp:usedBy |
machine learning researchers
chemoinformatics researchers |
| gptkbp:usedFor |
training machine learning models for quantum chemistry
|
| gptkbp:website |
https://quantum-machine.org/datasets/
|
| gptkbp:bfsParent |
gptkb:QM8
|
| gptkbp:bfsLayer |
7
|