• DAKOTA

  • Referenced in 62 articles [sw05202]
  • Framework for Design Optimization,Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis, The Dakota (Design Analysis ... with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods ... mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement...
  • ALEA

  • Referenced in 37 articles [sw10167]
  • methods and low-rank approximations in uncertainty quantification. ALEA is intended as a research framework ... numerical methods in Uncertainty Quantification (UQ). Its emphasis lies on: generalised polynomial chaos (gpc) methods...
  • UQLab

  • Referenced in 18 articles [sw19740]
  • 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 ... Chair of Risk, Safety and Uncertainty Quantification at ETH Zurich, and decided to gather ... community regarding the fundamental aspects of uncertainty quantification. The first closed beta version is online...
  • QUESO

  • Referenced in 21 articles [sw10555]
  • 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...
  • Virtual library

  • Referenced in 15 articles [sw27598]
  • MATLAB and R: Optimization, Emulation/ Prediction, Uncertainty Quantification, Multi Fidelity Simulation, Calibration/ Tuning, Screening, Integration...
  • Chaospy

  • Referenced in 8 articles [sw31225]
  • source tool for designing methods of uncertainty quantification. The paper describes the philosophy, design, functionality ... Python software toolbox Chaospy for performing uncertainty quantification via polynomial chaos expansions and Monte Carlo ... construct new, tailored algorithms for uncertainty quantification. For example, a Chaospy user ... rules, sampling schemes, and statistical metrics for uncertainty analysis. In addition, the software introduces some...
  • Pi4U

  • Referenced in 7 articles [sw18320]
  • high performance computing framework for Bayesian uncertainty quantification of complex models. We present Pi4U ... extensible framework, for non-intrusive Bayesian Uncertainty Quantification and Propagation (UQ+P) of complex...
  • FATODE

  • Referenced in 7 articles [sw11044]
  • estimation, data assimilation, optimal control, and uncertainty quantification...
  • Open TURNS

  • Referenced in 4 articles [sw12837]
  • Open TURNS: An industrial software for uncertainty quantification in simulation. The needs to assess robust ... industrial simulation challenge: to take uncertainties into account when dealing with complex numerical simulation frameworks ... different sections of this paper: uncertainty quantification, uncertainty propagation, sensitivity analysis and metamodeling. A section...
  • ALSVID-UQ

  • Referenced in 5 articles [sw12836]
  • Monte Carlo Finite Volume solver for uncertainty quantification in hyperbolic systems of conservation laws...
  • Exa-Dune

  • Referenced in 5 articles [sw32962]
  • grained parallelism offered by multiscale and uncertainty quantification methods where we have focused...
  • Stokhos

  • Referenced in 4 articles [sw20456]
  • Stokhos Stochastic Galerkin Uncertainty Quantification Methods...
  • IPP Toolbox

  • Referenced in 3 articles [sw09589]
  • collection of methods for uncertainty quantification and propagation using Dempster-Shafer Theory and imprecise probabilities ... provides all necessary functions to conduct an uncertainty analysis in the imprecise probabilistic framework ... helpful functions. Methods for the quantification of uncertainty by imprecise distributions and the propagation through...
  • TChem

  • Referenced in 4 articles [sw12714]
  • reaction parameters for sensitivity analysis and uncertainty quantification. The library also contains several functions that...
  • PIFISS

  • Referenced in 4 articles [sw10687]
  • associated with the project ”Uncertainty quantification in computer simulations of groundwater flow problems with emphasis...
  • UQToolbox

  • Referenced in 2 articles [sw20360]
  • UQToolbox: Tools for Uncertainty Quantification. This is a collection of tools for Uncertainty Quantification. Features...
  • COSSAN-X

  • Referenced in 2 articles [sw26340]
  • codes with the advanced tools of Uncertainty Quantification. By taking account of uncertainty/variability calculation results ... more realistic. Without Uncertainty Quantification, only a single value of the results can be obtained ... possible range of the results due to uncertainties...
  • muq

  • Referenced in 2 articles [sw33064]
  • Uncertainty Quantification (MUQ) library. In a nutshell, MUQ is a collection of tools for constructing ... models and a collection of uncertainty quantification (UQ)–focused algorithms for working on those models...
  • UQTk

  • Referenced in 4 articles [sw21917]
  • libraries and tools for the quantification of uncertainty in numerical model predictions. Version 3.0.4 offers...
  • BATMAN

  • Referenced in 1 article [sw29121]
  • Bayesian Analysis Tool for Modelling and uncertAinty quaNtification. It is a Python module distributed under ... statistical analysis (sensitivity analysis, Uncertainty Quantification, moments) based on non-intrusive ensemble experiment using ... Improvement), Sensitivity/Uncertainty Analysis (SA, UA) and Uncertainty Quantification (UQ), Visualization in n-dimensions (HDR, Kiviat...