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About
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.. _about:

Overview
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The Python Toolkit for Uncertainty Quantification (PyTUQ) is a Python-only set of tools designed for uncertainty quantification. Key PyTUQ capabilities include, but are not limited to:

- Methods for Gaussian process regression
- Global sensitivity analysis methods
- SVD-based dimensionality reduction techniques
- Karhunen-Loeve expansions
- Various methods for linear regression
- Bayesian compressive sensing techniques
- MCMC classes for calibration and parameter inference
- Classes and transformations for multivariate random variables
- Neural network and polynomial chaos expansion surrogate model construction
- Utilities including decorators, test functions, integration classes, and workflows

Authors
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- Khachik Sargsyan
- Bert Debusschere
- Emilie Grace Baillo

Acknowledgements
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This work is supported by the Scientific Discovery through Advanced Computing (SciDAC) Program under the Office of Science at the U.S. Department of Energy. 

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.