Introduces an information-matching approach based on the Fisher Information Matrix for optimal experimental design and active learning to select informative training data for models with sloppy parameters.
EDIP model for Si developed by Justo et al. (1998) v002,
2 Pith papers cite this work. Polarity classification is still indexing.
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Introduces UQ extension to KLIFF using PTMCMC to quantify uncertainty from parameter variation and IP functional form inadequacy, demonstrated on Stillinger-Weber potential for silicon.
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An information-matching approach to optimal experimental design and active learning
Introduces an information-matching approach based on the Fisher Information Matrix for optimal experimental design and active learning to select informative training data for models with sloppy parameters.
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Extending OpenKIM with an Uncertainty Quantification Toolkit for Molecular Modeling
Introduces UQ extension to KLIFF using PTMCMC to quantify uncertainty from parameter variation and IP functional form inadequacy, demonstrated on Stillinger-Weber potential for silicon.