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Gaussian approximations in filters and smoothers for data assimilation

Tellus. Series A, Dynamic meteorology and oceanography, 2019-01, Vol.71 (1), p.1600344

2019

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Bias Corrected Estimation of Paleointensity (BiCEP): An Improved Methodology for Obtaining Paleointensity Estimates

Geochemistry, geophysics, geosystems : G3, 2021-08, Vol.22 (8), p.n/a

2021

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What the collapse of the ensemble Kalman filter tells us about particle filters

Tellus. Series A, Dynamic meteorology and oceanography, 2017-01, Vol.69 (1), p.1283809

2017

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Eigenvector-spatial localisation

Tellus. Series A, Dynamic meteorology and oceanography, 2021-01, Vol.73 (1), p.1-18

2021

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Thermal Resolution of Unblocking Temperatures (TROUT): A Method for “Unmixing” Multi‐Component Magnetizations

Geochemistry, geophysics, geosystems : G3, 2023-06, Vol.24 (6), p.n/a

2023

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Using global Bayesian optimization in ensemble data assimilation: parameter estimation, tuning localization and inflation, or all of the above

Tellus. Series A, Dynamic meteorology and oceanography, 2021-01, Vol.73 (1), p.1-16

2021

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Coarse predictions of dipole reversals by low-dimensional modeling and data assimilation

Physics of the earth and planetary interiors, 2017-01, Vol.262 (C), p.8-27

2017

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A Bayesian Approach for Statistical–Physical Bulk Parameterization of Rain Microphysics. Part II: Idealized Markov Chain Monte Carlo Experiments

Journal of the atmospheric sciences, 2020-03, Vol.77 (3), p.1043-1064

2020

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High‐Dimensional Covariance Estimation From a Small Number of Samples

Journal of advances in modeling earth systems, 2024-09, Vol.16 (9), p.n/a

2024

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A canonical form of the equation of motion of linear dynamical systems

Proceedings of the Royal Society. A, Mathematical, physical, and engineering sciences, 2018-03, Vol.474 (2211), p.20170809-20170809

Royal Society (Great Britain), 2018

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A Theory for Why Even Simple Covariance Localization Is So Useful in Ensemble Data Assimilation

Monthly weather review, 2023-03, Vol.151 (3), p.717-736

2023

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How Sampling Errors in Covariance Estimates Cause Bias in the Kalman Gain and Impact Ensemble Data Assimilation

Monthly weather review, 2023-09, Vol.151 (9), p.2413-2426

2023

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To what extent is your data assimilation scheme designed to find the posterior mean, the posterior mode or something else?

Tellus. Series A, Dynamic meteorology and oceanography, 2016-12, Vol.68 (1), p.30625-17

2016

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Liquid water in the Martian mid-crust

Proceedings of the National Academy of Sciences - PNAS, 2024-08, Vol.121 (35)

2024

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Implicit Sampling for Path Integral Control, Monte Carlo Localization, and SLAM

Journal of dynamic systems, measurement, and control, 2015-05, Vol.137 (5)

Morzfeld, Matthias

2015

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Uncertainty quantification for regularized inversion of electromagnetic geophysical data—Part I: motivation and theory

Geophysical journal international, 2022-07, Vol.231 (2), p.1057-1074

2022

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Uncertainty quantification for regularized inversion of electromagnetic geophysical data – Part II: application in 1-D and 2-D problems

Geophysical journal international, 2022-07, Vol.231 (2), p.1075-1095

2022

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Implicit Sampling, with Application to Data Assimilation

Chinese annals of mathematics. Serie B, 2013, Vol.34 (1), p.89-98

2013

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Estimating parameters of the nonlinear cloud and rain equation from a large-eddy simulation

Physica. D, 2020-09, Vol.410, p.132500, Article 132500

2020

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A random map implementation of implicit filters

Journal of computational physics, 2012-02, Vol.231 (4), p.2049-2066

2012

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A Bayesian approach to calibrating hydrogen flame kinetics using many experiments and parameters

Combustion and flame, 2019-07, Vol.205, p.305-315

2019

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A Bayesian approach to calibrating hydrogen flame kinetics using many experiments and parameters

Combustion and flame, 2019-04, Vol.205 (C)

2019

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Limitations of polynomial chaos expansions in the Bayesian solution of inverse problems

Journal of computational physics, 2015-02, Vol.282 (C), p.138-147

2015

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Implicit Particle Methods and Their Connection with Variational Data Assimilation

Monthly weather review, 2013-06, Vol.141 (6), p.1786-1803

2013

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The decoupling of damped linear systems in oscillatory free vibration

Journal of sound and vibration, 2009-07, Vol.324 (1), p.408-428

2009

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Gaussian approximations in filters and smoothers for data assimilation

Bias Corrected Estimation of Paleointensity (BiCEP): An Improved Methodology for Obtaining Paleointensity Estimates

What the collapse of the ensemble Kalman filter tells us about particle filters

Eigenvector-spatial localisation

Thermal Resolution of Unblocking Temperatures (TROUT): A Method for “Unmixing” Multi‐Component Magnetizations

Using global Bayesian optimization in ensemble data assimilation: parameter estimation, tuning localization and inflation, or all of the above

Coarse predictions of dipole reversals by low-dimensional modeling and data assimilation

A Bayesian Approach for Statistical–Physical Bulk Parameterization of Rain Microphysics. Part II: Idealized Markov Chain Monte Carlo Experiments

High‐Dimensional Covariance Estimation From a Small Number of Samples

A canonical form of the equation of motion of linear dynamical systems

A Theory for Why Even Simple Covariance Localization Is So Useful in Ensemble Data Assimilation

How Sampling Errors in Covariance Estimates Cause Bias in the Kalman Gain and Impact Ensemble Data Assimilation

To what extent is your data assimilation scheme designed to find the posterior mean, the posterior mode or something else?

Liquid water in the Martian mid-crust

Implicit Sampling for Path Integral Control, Monte Carlo Localization, and SLAM

Uncertainty quantification for regularized inversion of electromagnetic geophysical data—Part I: motivation and theory

Uncertainty quantification for regularized inversion of electromagnetic geophysical data – Part II: application in 1-D and 2-D problems

Implicit Sampling, with Application to Data Assimilation

Estimating parameters of the nonlinear cloud and rain equation from a large-eddy simulation

A random map implementation of implicit filters

A Bayesian approach to calibrating hydrogen flame kinetics using many experiments and parameters

A Bayesian approach to calibrating hydrogen flame kinetics using many experiments and parameters

Limitations of polynomial chaos expansions in the Bayesian solution of inverse problems

Implicit Particle Methods and Their Connection with Variational Data Assimilation

The decoupling of damped linear systems in oscillatory free vibration

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