Participation by invitation only.
This workshop will take place at SAMSI in Research Triangle Park, NC.
This workshop is intended to bring together active participants of Working Group I, The Statistical Inverse Problems group, which is run as a part of the 2016-2017 Program on Optimization.The areas of particular interest include sampling techniques for parameter estimation for large-scale Bayesian inverse problems, quantification of uncertainty, and optimal design of experiments for Bayesian inverse problems governed by Partial Differential Equations (PDE). Target applications include a wide class of problems ranging from the geosciences to medical imaging.
There are two main themes of this workshop:
- Optimal experimental design, which seeks to control experimental parameters to maximize the information gain about the estimated parameters of interest, subject to budget or physical constraints.
- Novel sampling techniques and the use of reduced order models to effectively sample high-dimensional distributions.
Questions: email firstname.lastname@example.org