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by fock 2162 days ago
well, this is not predicting "quantum mechanics energies", it's just parametrizing the molecular bond interaction potential with a neural network instead of an analytic function (such as e.g. a Lennard-Jones potential).

It's nice, but not really quantum-mechanics level (which is maybe HF, DFT or coupled cluster), which takes a lot more cycles (but also allows to optimize geometries without knowing wether a bond exists)

1 comments

These neural network models do not need to know whether a bond exists - in fact, they have no concept of bond topology. They are designed to be a drop-in replacement for DFT in terms of energies and forces. The only inputs are XYZ coordinates and chemical element labels for the nuclei (and, in the near future, net charge of the system).
with the non-bonded interactions parametrized with dimers it might work... sometimes (might be good enough for a lot of things though)