Title: Combining Bayesian inference with data-consistent inversion: Leveraging population-level information to construct informative priors
Abstract: Computational models underpin many important applications at Sandia, such as additive manufacturing, nuclear waste repository management, and structural dynamics. However, such models often contain uncertain or unknown parameters that must be estimated from observational data by solving an inverse problem. Bayesian inference is a popular approach to inverse problems, but when data is limited (as is often the case for Sandia applications), a highly informative prior is needed; in practice, the physical knowledge required to construct such priors may not be available. Consequently, this work presents an alternative, novel approach for leveraging data from “population” of related experiments or physical assets to construct highly informative Bayesian priors. Specifically, we use a more recently developed inversion technique, known as data-consistent inversion (DCI), to estimate properties of a given population. Combining DCI with Bayesian inference in this way is shown to improve the inference process overall, further reducing model parameter uncertainty. This talk will provide an overview of both Bayesian inference and data-consistent inversion, illustrate how such inversion techniques can be combined, and demonstrate the combined approach for a computational mechanics exemplar governed by partial differential equations (PDEs).
Bio:
Rebekah (Bekah) White is a senior member of technical staff at Sandia National Labs, where she has been for the past three years. She received her PhD in applied mathematics from North Carolina State University in 2021, with her thesis work investigating the use of inverse problems to estimate, from ultrasound data, the pore distribution in human bones – a first step towards developing non-invasive approaches to diagnose bone diseases such as osteoporosis. Since being at Sandia, her area of work has been in uncertainty quantification, where she focuses primarily on inverse problems, sensitivity analysis, and optimal experimental design.
Bekah will be here September 30-October 2 and is willing to meet with faculty/students during that time. In particular, if you are interested in working at Sandia and/or have questions about working at the National Labs in general, she is happy to meet and talk about it.