Introduction
The UQ Toolkit (UQTk) is a collection of libraries and tools for the quantification of uncertainty in numerical model predictions. Version 3.1.x 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.
Authors
The UQ toolkit is the result of contributions by many people. The key authors of UQTk are (alphabetical by first name):
- Bert Debusschere, Sandia National Laboratories
- Caitlin Curry, Sandia National Laboratories
- Cosmin Safta, Sandia National Laboratories
- Katherine Johnston, Sandia National Laboratories
- Kenny Chowdhary, Sandia National Laboratories
- Khachik Sargsyan, Sandia National Laboratories
- Luke Boll, Sandia National Laboratories
- Mohammad Khalil, Sandia National Laboratories
- Prashant Rai, Sandia National Laboratories
- Tiernan Casey, Sandia National Laboratories
- Xiaoshu Zeng, University of Southern California
Beyond the authors listed above, there is a long and continually growing list of coworkers, students and visitors who have contributed to UQTk over the years. This list includes, but is not limited to (alphabetical by first name):
- Habib Najm, Sandia National Laboratories
- Helgi Adalsteinsson, Google
- Majid Latif, Sysco
- Olivier Le Maître, LIMSI-CNRS
- Omar Knio, KAUST
- Roger Ghanem, University of Southern California
- Sarah Castorena
- Sarah de Bord
- Xun Huan, University of Michigan
Download
The UQ Toolkit is released as a C++/Python open source library under the BSD 3-Clause License. The latest version can be downloaded from Github at https://github.com/sandialabs/UQTk.
For more information, to ask questions, or point of bugs, please post a message in the github discussions board for UQTk, or submit a github issue.