Machine learning-accelerated quantum mechanics-based atomistic simulations for industrial applications. - Tobias Morawietz; Nongnuch Artrith (J. Comput. Aided Mol. Des., 2021)

Strategies for the construction of machine-learning potentials for accurate and efficient atomic-scale simulations. - April M. Miksch; Tobias Morawietz; Johannes Kästner; Alexander Urban; Nongnuch Artrith (Mach. Learn. Sci. Technol., 2021)

A practical guide to machine learning interatomic potentials - Status and future. - Ryan Jacobs; Dane Morgan; Siamak Attarian; Jun Meng; Chen Shen; Zhenghao Wu; Clare Yijia Xie; Julia H. Yang; Nongnuch Artrith; Ben Blaiszik; Gerbrand Ceder; Kamal Choudhary; et al. (CoRR, 2025)