interatomic-potentials

Active Learning for SNAP Interatomic Potentials via Bayesian Predictive Uncertainty

Bayesian inference with a simple Gaussian error model is used to efficiently compute prediction variances for energies, forces, and stresses in the linear SNAP interatomic potential. The prediction variance is shown to have a strong correlation with …

Model Error Estimation for Active Learning of Interatomic Potential Models

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FitSNAP: Atomistic machine learning with LAMMPS

Uncertainty Quantification of Machine Learning Interatomic Potential Models

Poster

Model Error Estimation and Uncertainty Quantification of Machine Learning Interatomic Potentials

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UQ and Model Error Estimation for Machine Learning Interatomic Potentials

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Quantification and Propagation of Uncertainties in Machine Learning Interatomic Potentials for Molecular Dynamics

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Bayesian Inference of Interatomic Potentials

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Active Learning and Uncertainty Quantification for Machine Learning Interatomic Potentials

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Active Learning for Linearly Parameterized Interatomic Potentials

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