QeMFi: A Multifidelity Dataset of Quantum Chemical Properties of Diverse Molecules

This is the QeMFi (Quantum chemistry MultiFidelity) dataset (previously CheMFi, name updated post peer review process) generated for the molecules of the WS22 database. Multifidelity machine learning (MFML) for quantum chemical properties involves building a composite model using various fidelities as opposed to a single fidelity. This dataset is presented to the community as a collection of multifidelity data for various quantum chemical properties for benchmarking of future MFML models. The README.md file contains more details about this dataset and use-cases.