SIAMUQ16 - Slides Minisymp Software4UQ: Difference between revisions
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* [http://www5.in.tum.de/persons/neckel/siamuq16_slides_minisymp/2016_chaospy_tennoe.pdf D. Tennoe: Chaospy: A Modular Implementation of Polynomial Chaos Expansions and Monte Carlo Methods] | * [http://www5.in.tum.de/persons/neckel/siamuq16_slides_minisymp/2016_chaospy_tennoe.pdf D. Tennoe: Chaospy: A Modular Implementation of Polynomial Chaos Expansions and Monte Carlo Methods] | ||
* [http://www5.in.tum.de/persons/neckel/siamuq16_slides_minisymp/2016_dakota_Adams.pdf P. Hough: Recent Advances in Dakota UQ] | * [http://www5.in.tum.de/persons/neckel/siamuq16_slides_minisymp/2016_dakota_Adams.pdf P. Hough: Recent Advances in Dakota UQ] | ||
* [www.smartuq.com P. Qian: Handling Large-Scale Uncertainty Quantification with SmartUQ] | * [http://www.smartuq.com P. Qian: Handling Large-Scale Uncertainty Quantification with SmartUQ] | ||
[http://meetings.siam.org/sess/dsp_programsess.cfm?SESSIONCODE=22284 MS 72] | [http://meetings.siam.org/sess/dsp_programsess.cfm?SESSIONCODE=22284 MS 72] | ||
* <!--[http://www5.in.tum.de/persons/neckel/siamuq16_slides_minisymp/2016_chaospy_tennoe.pdf--> S. Marelli: Advancements in the Uqlab Framework for Uncertainty Quantification | * <!--[http://www5.in.tum.de/persons/neckel/siamuq16_slides_minisymp/2016_chaospy_tennoe.pdf--> S. Marelli: Advancements in the Uqlab Framework for Uncertainty Quantification | ||
* [http://www5.in.tum.de/persons/neckel/siamuq16_slides_minisymp/2016_psuade_Tong.pdf C. Tong: PSUADE: A Software Toolkit for Uncertainty Quantification] | * [http://www5.in.tum.de/persons/neckel/siamuq16_slides_minisymp/2016_psuade_Tong.pdf C. Tong: PSUADE: A Software Toolkit for Uncertainty Quantification] | ||
* [http://www5.in.tum.de/persons/neckel/siamuq16_slides_minisymp/2016_chaospy_tennoe.pdf Q. Duan: Uncertainty Quantification Python Laboratory (UQ-PyL) – A GUI For Parametric Uncertainty Analysis of Large Complex Dynamical Models] | * [http://www5.in.tum.de/persons/neckel/siamuq16_slides_minisymp/2016_chaospy_tennoe.pdf Q. Duan: Uncertainty Quantification Python Laboratory (UQ-PyL) – A GUI For Parametric Uncertainty Analysis of Large Complex Dynamical Models] | ||
Revision as of 15:33, 27 April 2016
At conference on Uncertainty Quantification 2016, Dirk Pflüger and Tobias Neckel organised a minisymposium on Software for UQ.
The presentations of most of the speakers are collected here, in the order of appearance:
- D. Pflüger: Adaptive Sparse Grids for UQ with SG++
- B. Debusschere: UQTk: a C++/Python Toolkit for Uncertainty Quantification
- E. Patelli: Opencossan: A Open Matlab Tool for Dealing with Randomness, Imprecision and Vagueness
- A. Davis: MUQ (MIT Uncertainty Quantification): A Flexible Software Framework for Algorithms and Applications
- D. McDougall: The Parallel C++ Statistical Library Queso: Quantification of Uncertainty for Estimation, Simulation and Optimization
- D. Tennoe: Chaospy: A Modular Implementation of Polynomial Chaos Expansions and Monte Carlo Methods
- P. Hough: Recent Advances in Dakota UQ
- P. Qian: Handling Large-Scale Uncertainty Quantification with SmartUQ
- S. Marelli: Advancements in the Uqlab Framework for Uncertainty Quantification
- C. Tong: PSUADE: A Software Toolkit for Uncertainty Quantification
- Q. Duan: Uncertainty Quantification Python Laboratory (UQ-PyL) – A GUI For Parametric Uncertainty Analysis of Large Complex Dynamical Models