5 days ago · This paper considers the problem of optimal placement of actuators and sensors with the aim of maximizing the data information in an experimental design with ...

6 days ago · Scalable optimal experimental design for large scale non-linear Bayesian inverse problems, Applied. Inverse Problems, July 8-12, 2019, Grenoble, France.

4 days ago · In this paper we survey the primary research, both theoretical and applied, in the area of robust optimization (RO).

4 days ago · Bayesian optimization for distributionally robust chance-constrained problem. In Proceedings of the 39th International Conference on Machine Learning ...

5 days ago · A FEBQR model is proposed under unknown lifetime data distribution. •. Factor indicator variables integrate factorial effect principles into lifetime model.

4 days ago · The A-optimal experimental design for model (1)allocates w∗= 1/(1 + √τ) ... Bayesian setup in nonlinear models to find optimal designs. In the latter ...

56 minutes ago · Several classical and Bayesian estimation techniques are presented to estimate the distribution parameters and the acceleration factor of the power half- ...

3 days ago · In this sense, it closely mimics the iterative design-make-test-analysis cycle of laboratory experiments to find optimized compounds for a given design task.

6 days ago · We develop an open-source Python-based Parameter Estimation Tool utilizing Bayesian Optimization (petBOA) with a unique wrapper interface for gradient-free ...

3 days ago · The Bayesian Cramér-Rao bound (CRB) provides a lower bound on the mean square error of any Bayesian estimator under mild regularity conditions.