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It has been great to collaborate with @tfmiller3 @ZhuoranQ @mattgwelborn @Caltech on #Deeplearning for #chemistry #AI4science We incorporate symmetries in atomic orbital structure and use #graph #NeuralNetworks >1000x speedup over traditional methods while preserving accuracyhttps://twitter.com/tfmiller3/status/1283928561166905344 …
We don't just use #NeuralNetworks in a naive way. We get low-cost features using semi-empirical electronic structure calculations: uses domain knowledge and also uses known symmetries in atomic orbitals. We show zero-shot generalization to much larger molecules than training data
Very interesting. Does this speedup include data synthesis and training time?
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