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

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

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....

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

Internet

https://hdl.handle.net/10356/163142

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