- Referenced in 212 articles
- systems with persistent additive and polytopic uncertainties. Users can add custom constraints, such as polytopic...
Robust Control Toolbox
- Referenced in 144 articles
- analyze the impact of plant model uncertainty on control system performance and identify worst-case...
- Referenced in 64 articles
- Oriented Framework for Design Optimization,Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis, The Dakota (Design ... optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion ... mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement...
- Referenced in 45 articles
- obtaining correct curve estimates by accounting for uncertainty in FPC decompositions. Additionally, pointwise and simultaneous ... bootstrap procedure is implemented to understand the uncertainty in principal component decomposition quantities. Our method...
- Referenced in 45 articles
- Kriging has just started to appear in uncertainty propagation  and reliability and studies ... exact interpolation and a local index of uncertainty on the prediction which can be used...
- Referenced in 44 articles
- Artificial Intelligence. Presents a theory of uncertainty, consistent with and combining the theories of probability ... inference to permit the inclusion of uncertainties such as probabilistic knowledge and fuzzy incompleteness. Describes...
- Referenced in 61 articles
- wide-spread methodologies to deal with uncertainty in real-world decision making problems, the computing...
- Referenced in 42 articles
- spectral methods and low-rank approximations in uncertainty quantification. ALEA is intended as a research ... framework for numerical methods in Uncertainty Quantification (UQ). Its emphasis lies on: generalised polynomial chaos...
- Referenced in 30 articles
- UQLab: The Framework for Uncertainty Quantification. UQLab is a Matlab-based software framework designed ... bring state-of-the art uncertainty quantification (UQ) techniques and algorithms to a large audience ... founded the Chair of Risk, Safety and Uncertainty Quantification at ETH Zurich, and decided ... scientific community regarding the fundamental aspects of uncertainty quantification. The first closed beta version...
- Referenced in 26 articles
- toolbox for Matlab for building LFT-based uncertainty models and for LFT-based gain scheduling ... object definition supporting a large class of uncertainty descriptions: continuous- and discrete-time uncertain models ... regular and singular parametric expressions, more general uncertainty blocks (nonlinear, time-varying, etc.). By associating ... names to uncertainty blocks the reusability of generated LFT-representations and the user friendliness...
- Referenced in 41 articles
- default rates in order to capture the uncertainty in the level of default rates. Often...
- Referenced in 39 articles
- over worlds with unknown objects and identity uncertainty. BLOG unifies and extends several existing approaches...
- Referenced in 36 articles
- serve as a quantification of the predictive uncertainty. A very promising solution is to combine...
- Referenced in 34 articles
- rich framework for sequential decision-making under uncertainty in stochastic domains. However, solving a POMDP...
- Referenced in 24 articles
- biology. MOTIVATION: There are several levels of uncertainty involved in the mathematical modelling of biochemical ... There often may be a degree of uncertainty about the values of kinetic parameters, about...
- Referenced in 23 articles
- supply, transformation and distribution optimization under uncertainty. The authors present a modeling framework ... Transformation and Distribution (STD) scheduling problem under uncertainty on the product demand, spot supply cost...
- Referenced in 32 articles
- formally justifies the “optimism under uncertainty” bias used in many RL algorithms...
- Referenced in 18 articles
- tabling and answer subsumption for reasoning under uncertainty. Many real world domains require the representation ... measure of uncertainty. The most common such representation is probability, and the combination of probability ... logic programs adopt a simpler metric of uncertainty than probability.par Each of these approaches -- general ... different domains depending on the form of uncertainty to be represented, on the form...
- Referenced in 22 articles
- Parallel C++ Statistical Library ‘QUESO’: Quantification of Uncertainty for Estimation, Simulation and Optimization. QUESO ... programming constructs supporting research into the uncertainty quantification (UQ) of models and their predictions...