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4 papers · 2 filters
Inverse molecular design and parameter optimization with Hückel theory using automatic differentiation
R. A. Vargas-Hernández, K. Jorner, R. Pollice +1
Semi-empirical quantum chemistry has recently seen a renaissance with applications in high-throughput virtual screening and machine learning. The simplest semi-empirical model stil…
Towards DMC accuracy across chemical space with scalable -QML
Bing Huang, O. Anatole von Lilienfeld, Jaron T. Krogel +1
In the past decade, quantum diffusion Monte Carlo (DMC) has been demonstrated to successfully predict the energetics and properties of a wide range of molecules and solids by numer…
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…
Relative energies without electronic perturbations via Alchemical Integral Transform
Simon León Krug, Guido Falk von Rudorff, O. Anatole von Lilienfeld
We show that the energy of a perturbed system can be fully recovered from the unperturbed system's electron density. We derive an alchemical integral transform by parametrizing spa…