Significance of the chemical environment of an element in nonadiabatic molecular dynamics: feature selection and dimensionality reduction with machine learning

• Main Authors: How, Wei Bin, Wang, Bipeng, Chu, Weibin, Tkatchenko, Alexandre, Prezhdo, Oleg V.
• Other Authors: School of Physical and Mathematical Sciences
• Format: Article
• Language: English
• Published: 2022
• Subjects: Science::Chemistry; Dimensionality Reduction; Machine-Learning
• Online Access: https://hdl.handle.net/10356/163142
• Institution: Nanyang Technological University

Using supervised and unsupervised machine learning (ML) on features generated from nonadiabatic (NA) molecular dynamics (MD) trajectories under the classical path approximation, we demonstrate that mutual information with the NA Hamiltonian can be used for feature selection and model simplification....