Foundry - Approaching QMC quality energetics throughout chemical space using scalable quantum machine learning

This dataset contains summary inputs and outputs generated for the Paper "Approaching QMC quality energetics throughout chemical space using scalable quantum machine learning" By B. Huang, O. Anatole von Lilienfeld, J. T. Krogel and A. Benali. Included in the dataset are energies for 1175 molecules calculated with varying methods, associated error calculations, and molecular structures in XYZ and pymatgen Molecule formats. Raw data for these calculations are available at https://doi.org/10.18126/hxlp-v732