My name is Arved Bartuska, I am a Ph.D. student at the Chair of Mathematics for Uncertainty Quantification. The topic of my thesis is “Hierarchical Methods for Bayesian Optimal Experimental Design”.
Bayesian experimental design aims at determining an experimental setup for which the information obtained about certain parameters of interest is maximized. Uncertainty stemming from the model parameters is quantified and efficient algorithms are derived.
- Bayesian experimental design
- Laplace approximation
- Nuisance uncertainty
- Monte Carlo
- Quasi Monte Carlo.
Bartuska, A., Espath, L., and Tempone, R. “Small-noise approximation for Bayesian optimal experimental design with nuisance uncertainty”. Computer Methods in Applied Mechanics and Engineering. 399, 115320, 2022.[DOI:10.1016/j.cma.2022.115320]
Talks and presentations
|15/05/2022 - 28/05/2022||Small-noise approximation for Bayesian optimal experimental design with nuisance uncertainty||King Abdullah University of Science and Technology, Saudi Arabia (Hybrid)|
|12/04/2022 - 12/04/2022||Laplace Approximation for Bayesian Optimal Experimental Design with Nuisance Uncertainty||Atlanta (Hybrid)|