3 papers
stat.ME2025
Optimal Experimental Design Criteria for Data-Consistent Inversion
Troy Butler, John Jakeman, Michael Pilosov +2
The ability to design effective experiments is crucial for obtaining data that can substantially reduce the uncertainty in the predictions made using computational models. An optim…
eess.SY2024
A switching Kalman filter approach to online mitigation and correction of sensor corruption for inertial navigation
Artem Mustaev, Nicholas Galioto, Matt Boler +3
This paper introduces a novel approach to detect and address faulty or corrupted external sensors in the context of inertial navigation by leveraging a switching Kalman Filter comb…
stat.CO2024
Grouped approximate control variate estimators
Alex A. Gorodetsky, John D. Jakeman, Michael S. Eldred
This paper analyzes the approximate control variate (ACV) approach to multifidelity uncertainty quantification in the case where weighted estimators are combined to form the compon…