SIAMUQ18 - Slides Minisymp Software4UQ
At the SIAM conference on Uncertainty Quantification 2018, Tobias Neckel and Dirk Pflüger organised a minisymposium on Software for UQ.
The presentations of most of the speakers are collected here, in the order of appearance:
- Dirk Pflüger: Data-driven, Adaptive Sparse Grids for UQ in SG++
- Brian Adams: Dakota: Explore and Predict with Confidence
- Michael Baudin: The Openturns Uncertainty Quantification Software
- Arnold Song: Bayesian Computation for Statistical and Physical Problems
- Jean-Baptiste Blanchard: URANIE: The Uncertainty and Optimization Platform
- Charles Tong: PSUADE: A Framework for Uncertainty Quantification and Optimization
- Michael McKerns: Mystic: Rigorous Model Certification and Engineering Design under Uncertainty
- Miroslav Stoyanov: Markov Chain Monte Carlo Sampling using GPU Accelerated Sparse Grids Surrogate Models
- Friedrich Menhorn: Integrating SNOWPAC in Dakota with Application to a Scramjet
- Jonathan Feinberg: Chaospy: A Pythonic Approach to Polynomial Chaos Expansion
- Florian Künzner/Tobias Neckel: Prediction and Reduction of Runtime in UQ Simulations on HPC Systems using Chaospy
- Bert Debusschere: UQTk - A Flexible Python/C++ Toolkit for Uncertainty Quantification
The above image shows the implementations (and corresponding locations) scheduled in the minisymposium which represents the majority of UQ software as of April 2018.
We plan to repeat this minisymposium at the next SIAM UQ in 2020. If your software is missing on this list and if you would like to contribute, please notify us.