Presentations for Geilo Winter School 2015
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Updated
Jan 23, 2018 - TeX
Presentations for Geilo Winter School 2015
Intention-aware control using stochastic expansion methods
Codes used for the results in the paper: Sensitivity Analysis for a long-time clogging simulation code.
A source code for the paper titled "Global Sensitivity Analysis using Polynomial Chaos Expansion on the Grassmann Manifold".
This suite is an ensemble of codes developed to conduct a global sensitivity analysis on an multimodal energy harvesting system with periodic excitation.
This repository includes Matlab codes/routines that were used in my Bachelor thesis entitled "Numerical Methods For Uncertainty Quantification In Option Pricing" that can be found in: https://www.researchgate.net/publication/330005261_Numerical_Methods_For_Uncertainty_Quantification_In_Option_Pricing.
Arbitrary Polynomial Chaos Toolkit
Generate orthogonal polynomials for arbitrary probability density functions
Evaluating model calibration methods for sensitivity analysis, uncertainty analysis, optimisation, and Bayesian inference
Probabilistic Response mOdel Fitting with Interactive Tools
Source code of: "Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models".
A Sensitivity and uncertainty analysis toolbox for Python based on the generalized polynomial chaos method
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