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Open Source Infrastructure for Differentiable Density Functional Theory. (arXiv:2309.15985v1 [cs.LG])

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Learning exchange correlation functionals, used in quantum chemistry
calculations, from data has become increasingly important in recent years, but
training such a functional requires sophisticated software infrastructure. For
this reason, we build open source infrastructure to train neural exchange
correlation functionals. We aim to standardize the processing pipeline by
adapting state-of-the-art techniques from work done by multiple groups. We have
open sourced the model in the DeepChem library to provide a platform for
additional research on differentiable quantum chemistry methods.

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