model-error

Stochastic Surrogates and Quantification of Model Errors in Earth System Models

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Model Error Embedding with Orthogonal Gaussian Processes

Computational models of complex physical systems often rely on simplifying assumptions which inevitably introduce model error, with consequent predictive errors. Given data on model observables, the estimation of parameterized model-error …

Inverse Modeling via Bayesian Inference

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Uncertainty Quantification in Computational Science -- from Physical Models to Neural Networks

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Embedded Framework for Model Error Quantification and Propagation

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Quantification of Modeling Uncertainty in the Rayleigh Damping Model

Abstract Understanding and accurately characterizing energy dissipation mechanisms in civil structures during earthquakes is an important element of seismic assessment and design. The most commonly used model is attributed to Rayleigh. This paper …

Model Error Estimation for Active Learning of Interatomic Potential Models

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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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