Enhancing Robustness of Neural Network Interatomic Potentials through Sampling Methods and Uncertainty Quantification

Enhancing Robustness of Neural Network Interatomic Potentials through Sampling Methods and Uncertainty Quantification

Neural network interatomic potentials (NNIPs) are a significant advancement in computational materials science and chemistry for their ability to accurately approximate the potential energy surface (PES) of atomic systems with significantly reduced computational costs compared to quantum mechanical...

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Bibliographic Details
Main Author:	Tan, Aik Rui
Other Authors:	Gómez-Bombarelli, Rafael
Format:	Thesis
Published:	Massachusetts Institute of Technology 2024
Online Access:	https://hdl.handle.net/1721.1/155357 https://orcid.org/0000-0001-6731-5531

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