The UQTk C++/Python Toolkit for Uncertainty Quantification: Overview and Applications
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Jump to search filtersUQTk Version 3.1.2 User Manual
The UQ Toolkit (UQTk) is a collection of libraries and tools for the quantification of uncertainty in numerical model predictions. Version 3.1.2 offers intrusive and non-intrusive methods for propagating input uncertainties through computational models, tools for sensitivity analysis, methods for sparse surrogate construction, and Bayesian inference tools for inferring parameters from experimental data. This manual discusses the download and installation process for UQTk, provides pointers to the UQ methods used in the toolkit, and describes some of the examples provided with the toolkit.
Inference of Hydrogen RedOx Reactions Models using Bayesian Compressive Sensing
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UQTk Version 3.1.1 User Manual
The UQ Toolkit (UQTk) is a collection of libraries and tools for the quantification of uncertainty in numerical model predictions. Version 3.1.1 offers intrusive and non-intrusive methods for propagating input uncertainties through computational models, tools for sensitivity analysis, methods for sparse surrogate construction, and Bayesian inference tools for inferring parameters from experimental data. This manual discusses the download and installation process for UQTk, provides pointers to the UQ methods used in the toolkit, and describes some of the examples provided with the toolkit.
UQTk A C++/Python Toolkit for Uncertainty Quantification: Overview and Applications
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Refactoring MCMC for Uncertainty Quantification using Abstract Datatypes and Class Inheritance
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