3 citations · 3 across the 1 of their papers we have counts for
5 papers
Ab initio machine learning in chemical compound space
Bing Huang, O. Anatole von Lilienfeld
Chemical compound space (CCS), the set of all theoretically conceivable combinations of chemical elements and (meta-)stable geometries that make up matter, is colossal. The first p…
Dictionary of 140k GDB and ZINC derived AMONs
Bing Huang, O. Anatole von Lilienfeld
We present all {\bf A}mons for {\bf G}DB and {\bf Z}inc data-bases using no more than 7 non-hydrogen atoms (AGZ7)---a calculated organic chemistry building-block dictionary based o…
Impact of non-normal error distributions on the benchmarking and ranking of Quantum Machine Learning models
Pascal Pernot, Bing Huang, Andreas Savin
Quantum machine learning models have been gaining significant traction within atomistic simulation communities. Conventionally, relative model performances are being assessed and c…
Boosting quantum machine learning models with multi-level combination technique: Pople diagrams revisited
Peter Zaspel, Bing Huang, Helmut Harbrecht +1
Inspired by Pople diagrams popular in quantum chemistry, we introduce a hierarchical scheme, based on the multi-level combination (C) technique, to combine various levels of approx…
The fundamentals of quantum machine learning
Bing Huang, Nadine O. Symonds, O. Anatole von Lilienfeld
Within the past few years, we have witnessed the rising of quantum machine learning (QML) models which infer electronic properties of molecules and materials, rather than solving a…