Information Methods for Uncertainty Quantification and Performance Guarantees in Predictive Modeling
Abstract
The proposed research is the development of the foundations of Uncertainty Quantification for complex systems. The novelty of the proposal is a broad and general approach to the systematic development of UQ methods using tools from applied and computational probability, information theory, and quantum and statistical mechanics to assess and measure predictive bias for a range of quantities of interest and statistical estimators. Our methods can discriminate and assess multiple sources of model uncertainties, can treat models with multiple scales and those driven by rare events, and provide the first systematic approach for Uncertainty Quantification in quantum systems.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jul 24, 2019
- Source ID
- FA95501810530
Entities
People
- Paul Dupuis
Organizations
- Air Force Office of Scientific Research
- Brown University
- United States Air Force