Jindra Dušek

Artificial Intelligence (AI) has significantly influenced numerous scientific disciplines, including computational chemistry. This issue of CHIMIA highlights Swiss research groups working at the intersection of AI and computational chemistry, spanning both fundamental theory and practical applications

Abstract Accurate simulations of molecules require high-level electronic-structure theory in combination with rigorous methods for approximating the quantum dynamics. Machine-learning approaches can significantly reduce the computational expense of this workflow without any loss of accuracy. We discuss various methods for constructing potential energy surfaces including transfer learning, which requires a minimal number of expensive training points.