Outputs (18)

Bayesian inversion for in-situ thermal characterisation of walls in the presence of thermal anomalies (2024)
Journal Article
Iglesias, M., Li, X., Sovetova, M., & Wu, Y. (2024). Bayesian inversion for in-situ thermal characterisation of walls in the presence of thermal anomalies. Energy and Buildings, 319, Article 114558. https://doi.org/10.1016/j.enbuild.2024.114558

This paper develops a Bayesian inverse modelling framework for the in-situ characterisation of walls' thermal performance in the presence of thermal anomalies subject to uncertainty. For any given wall, the proposed framework uses in-situ contact mea... Read More about Bayesian inversion for in-situ thermal characterisation of walls in the presence of thermal anomalies.

Ensemble Kalman inversion of induced polarization data (2024)
Journal Article
Tso, C.-H. M., Iglesias, M., & Binley, A. (2024). Ensemble Kalman inversion of induced polarization data. Geophysical Journal International, 236(3), 1877-1900. https://doi.org/10.1093/gji/ggae012

This paper explores the applicability of ensemble Kalman inversion (EKI) with level-set parametrization for solving geophysical inverse problems. In particular, we focus on its extension to induced polarization (IP) data with uncertainty quantificati... Read More about Ensemble Kalman inversion of induced polarization data.

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..

Bayesian inversion algorithm for estimating local variations in permeability and porosity of reinforcements using experimental data (2021)
Journal Article
Matveev, M., Endruweit, A., Long, A., Iglesias, M., & Tretyakov, M. (2021). Bayesian inversion algorithm for estimating local variations in permeability and porosity of reinforcements using experimental data. Composites Part A: Applied Science and Manufacturing, 143, Article 106323. https://doi.org/10.1016/j.compositesa.2021.106323

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.