Assessing Conformer Energies using Electronic Structure and Machine Learning Methods
My first paper on assessing conformer energies using numerous different methods is now on ChemRxiv. We tested conventional computational techniques as well as the new kid on the block, machine learning. We found that machine learning methods, while currently having comparable accuracy to semiempirical methods, show great promise with future improvements in accuracy as well as GPU acceleration. To see more check out our interactive paper on Authorea.
