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On a Dynamic Variant of the Iteratively Regularized Gauss–Newton Method with Sequential Data (2023)
Journal Article
Chada, N. K., Iglesias, M., Lu, S., & Werner, F. (2023). On a Dynamic Variant of the Iteratively Regularized Gauss–Newton Method with Sequential Data. SIAM Journal on Scientific Computing, 45(6), A3020-A3046. https://doi.org/10.1137/22m1512442

For numerous parameter and state estimation problems, assimilating new data as they become available can help produce accurate and fast inference of unknown quantities. While most existing algorithms for solving those kind of ill-posed inverse prob... Read More about On a Dynamic Variant of the Iteratively Regularized Gauss–Newton Method with Sequential Data.

Ensemble Kalman inversion for magnetic resonance elastography. (2022)
Journal Article
Iglesias, M., McGrath, D. M., Tretyakov, M. V., & Francis, S. T. (2022). Ensemble Kalman inversion for magnetic resonance elastography. Physics in Medicine and Biology, 67(23), Article 235003. https://doi.org/10.1088/1361-6560/ac9fa1

Magnetic Resonance Elastography (MRE) is an MRI-based diagnostic method for measuring mechanical properties of biological tissues. MRE measurements are processed by an inversion algorithm to produce a map of the biomechanical properties. In this pape... Read More about Ensemble Kalman inversion for magnetic resonance elastography..

Adaptive regularisation for ensemble Kalman inversion (2020)
Journal Article
Iglesias, M. A., & Yang, Y. (2021). Adaptive regularisation for ensemble Kalman inversion. Inverse Problems, 37(2), Article 025008. https://doi.org/10.1088/1361-6420/abd29b

We propose a new regularisation strategy for the classical ensemble Kalman inversion (EKI) framework. The strategy consists of: (i) an adaptive choice for the regularisation parameter in the update formula in EKI, and (ii) criteria for the early stop... Read More about Adaptive regularisation for ensemble Kalman inversion.

Transform-based particle filtering for elliptic Bayesian inverse problems (2019)
Journal Article
Ruchi, S., Dubinkina, S., & Iglesias, M. A. (2019). Transform-based particle filtering for elliptic Bayesian inverse problems. Inverse Problems, 35(11), Article 115005. https://doi.org/10.1088/1361-6420/ab30f3

We introduce optimal transport based resampling in adaptive SMC. We consider elliptic inverse problems of inferring hydraulic conductivity from pressure measurements. We consider two parametrizations of hydraulic conductivity: by Gaussian random fiel... Read More about Transform-based particle filtering for elliptic Bayesian inverse problems.

Quantifying uncertainty in thermophysical properties of walls by means of Bayesian inversion (2018)
Journal Article
De Simon, L., Iglesias, M., Jones, B., & Wood, C. (2018). Quantifying uncertainty in thermophysical properties of walls by means of Bayesian inversion. Energy and Buildings, 177, 220-245. https://doi.org/10.1016/j.enbuild.2018.06.045

We introduce a computational framework to statistically infer thermophysical properties of any given wall from in-situ measurements of air temperature and surface heat fluxes. The proposed framework uses these measurements, within a Bayesian calibrat... Read More about Quantifying uncertainty in thermophysical properties of walls by means of Bayesian inversion.

Bayesian inversion in resin transfer molding (2018)
Journal Article
Iglesias, M., Park, M., & Tretyakov, M. (2018). Bayesian inversion in resin transfer molding. Inverse Problems, 34(10), Article 105002. https://doi.org/10.1088/1361-6420/aad1cc

We study a Bayesian inverse problem arising in the context of Resin Transfer Molding (RTM), which is a process commonly used for the manufacturing of fiber- reinforced composite materials. The forward model is described by a moving boundary problem i... Read More about Bayesian inversion in resin transfer molding.

Ensemble-marginalized Kalman filter for linear time-dependent PDEs with noisy boundary conditions: application to heat transfer in building walls (2018)
Journal Article
Iglesias, M., Sawlan, Z., Scavino, M., Tempone, R., & Woodard, C. (2018). Ensemble-marginalized Kalman filter for linear time-dependent PDEs with noisy boundary conditions: application to heat transfer in building walls. Inverse Problems, 34(7), https://doi.org/10.1088/1361-6420/aac224

In this work, we present the ensemble-marginalized Kalman filter (EnMKF), a sequential algorithm analo- gous to our previously proposed approach [1, 2], for estimating the state and parameters of linear parabolic partial differential equations in ini... Read More about Ensemble-marginalized Kalman filter for linear time-dependent PDEs with noisy boundary conditions: application to heat transfer in building walls.

Parameterizations for ensemble Kalman inversion (2018)
Journal Article
Chada, N., Iglesias, M., Lassi, R., & Stuart, A. M. (2018). Parameterizations for ensemble Kalman inversion. Inverse Problems, 34(5), https://doi.org/10.1088/1361-6420/aab6d9

The use of ensemble methods to solve inverse problems is attractive because it is a derivative-free methodology which is also well-adapted to parallelization. In its basic iterative form the method produces an ensemble of solutions which lie in the l... Read More about Parameterizations for ensemble Kalman inversion.

Filter based methods for statistical linear inverse problems (2017)
Journal Article
Iglesias, M., Lin, K., Shuai, L., & Stuart, A. M. (2017). Filter based methods for statistical linear inverse problems. Communications in Mathematical Sciences, 15(7), 1867–1896. https://doi.org/10.4310/CMS.2017.v15.n7.a4

Ill-posed inverse problems are ubiquitous in applications. Understanding of algorithms for their solution has been greatly enhanced by a deep understanding of the linear inverse problem. In the applied communities ensemble-based filtering methods hav... Read More about Filter based methods for statistical linear inverse problems.

Bayesian inferences of the thermal properties of a wall using temperature and heat flux measurements (2017)
Journal Article
Iglesias, M., Sawlan, Z., Scavino, M., Tempone, R., & Wood, C. J. (2018). Bayesian inferences of the thermal properties of a wall using temperature and heat flux measurements. International Journal of Heat and Mass Transfer, 116, https://doi.org/10.1016/j.ijheatmasstransfer.2017.09.022

The assessment of the thermal properties of walls is essential for accurate building energy simulations that are needed to make effective energy-saving policies. These properties are usually investigated through in-situ measurements of temperature an... Read More about Bayesian inferences of the thermal properties of a wall using temperature and heat flux measurements.

Hierarchical Bayesian level set inversion (2016)
Journal Article
Dunlop, M. M., Iglesias, M., & Stuart, A. M. (in press). Hierarchical Bayesian level set inversion. Statistics and Computing, 27(6), https://doi.org/10.1007/s11222-016-9704-8

The level set approach has proven widely successful in the study of inverse problems for inter- faces, since its systematic development in the 1990s. Re- cently it has been employed in the context of Bayesian inversion, allowing for the quantificatio... Read More about Hierarchical Bayesian level set inversion.

A Bayesian level set method for geometric inverse problems (2016)
Journal Article
Iglesias, M., Lu, Y., & Stuart, A. (2016). A Bayesian level set method for geometric inverse problems. Interfaces and Free Boundaries, 18(2), https://doi.org/10.4171/IFB/362

We introduce a level set based approach to Bayesian geometric inverse problems. In these problems the interface between different domains is the key unknown, and is realized as the level set of a function. This function itself becomes the object of t... Read More about A Bayesian level set method for geometric inverse problems.