8 citations · 8 across the 2 of their papers we have counts for
3 papers
Transfer Learning for Molecular Property Predictions from Small Data Sets
Thorren Kirschbaum, Annika Bande
Machine learning has emerged as a new tool in chemistry to bypass expensive experiments or quantum-chemical calculations, for example, in high-throughput screening applications. Ho…
Hydration structure of diamondoids from reactive force fields
Karol Palczynski, Thorren Kirschbaum, Annika Bande +1
Diamondoids are promising materials for applications in catalysis and nanotechnology. Since many of their applications are in aqueous environments, to understand their function it…
Machine learning frontier orbital energies of nanodiamonds
Thorren Kirschbaum, Börries von Seggern, Joachim Dzubiella +2
Nanodiamonds have a wide range of applications including catalysis, sensing, tribology and biomedicine. To leverage nanodiamond design via machine learning, we introduce the new da…