Learning Invariant Representations of Molecules for Atomization Energy Prediction

no code implementations • NeurIPS 2012 • Grégoire Montavon, Katja Hansen, Siamac Fazli, Matthias Rupp, Franziska Biegler, Andreas Ziehe, Alexandre Tkatchenko, Anatole V. Lilienfeld, Klaus-Robert Müller

The accurate prediction of molecular energetics in chemical compound space is a crucial ingredient for rational compound design.

BIG-bench Machine Learning