Reviews In Computational Chemistry

By J. Fuhrmann. 2017

297 citations recorded by the source corpus.

Subfields: Physical and Theoretical Chemistry

View Paper: https://www.semanticscholar.org/paper/527c57ec77ee85586311caadc3c8c28824135960

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Physical and Theoretical Chemistry

1. Rampi Ramprasad
2. V. Botu

Citations in the corpus

• Learning scheme to predict atomic forces and accelerate materials simulations (2015, methodology): “This concept is resonant with emerging data-driven (or “big data” [2–6]) approaches aimed at materials discovery in general [7, 8], as well as at accelerating materials simulations [9–13].”