292 citations · 632 across the 6 of their papers we have counts for
5 papers · 1 filter
Impact of noise on inverse design: The case of NMR spectra matching
Dominik Lemm, Guido Falk von Rudorff, O. Anatole von Lilienfeld
Despite its fundamental importance and widespread use for assessing reaction success in organic chemistry, deducing chemical structures from nuclear magnetic resonance (NMR) measur…
Improved decision making with similarity based machine learning: Applications in chemistry
Dominik Lemm, Guido Falk von Rudorff, O. Anatole von Lilienfeld
Despite the fundamental progress in autonomous molecular and materials discovery, data scarcity throughout chemical compound space still severely hampers the use of modern ready-ma…
SELFIES and the future of molecular string representations
Mario Krenn, Qianxiang Ai, Senja Barthel +28
Artificial intelligence (AI) and machine learning (ML) are expanding in popularity for broad applications to challenging tasks in chemistry and materials science. Examples include…
Ab initio machine learning of phase space averages
Jan Weinreich, Dominik Lemm, Guido Falk von Rudorff +1
Equilibrium structures determine material properties and biochemical functions. We propose to machine learn phase-space averages, conventionally obtained by {\em ab initio} or forc…
Machine learning based energy-free structure predictions of molecules (closed and open-shell), transition states, and solids
Dominik Lemm, Guido Falk von Rudorff, O. Anatole von Lilienfeld
The computational prediction of atomistic structure is a long-standing problem in physics, chemistry, materials, and biology. Within conventional force-field or {\em ab initio} cal…