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Surrogate models for UQ in complex systems
Isaac Newton Institute, Cambridge
5 - 9 February 2018
https://www.newton.ac.uk/event/unqw02
Registration for this workshop is open through to 5 December 2017.
Our modern treatment of predicting the behavior of physical and engineering problems relies on approximating solutions in terms of physical and stochastic domains, particularly in the case of uncertainty quantification (UQ), where the input data (coefficients, forcing terms, boundary conditions, geometry, etc) are affected by randomness. For higher resolution and accuracy, simulations must increase the number of deterministic and stochastic variables, and expend more effort resolving smooth or even discontinuous behavior within each individual component. Simulating the entire complex system at the level of fidelity that truly predicts the solution, remains elusive outside of idealized situations. To combat this resulting explosion in computational effort, surrogate models are employed to quickly and efficiently predict the input-output map of many complex simulations. As such, this workshop will be organized around a set of themes in which surrogate models have become an essential tool in enabling and accelerating UQ for a variety of problems, including:
1. High-dimensional stochastic systems;
2. Inference, optimization, and control in the presence of uncertainty;
3. Stochastic multi-scale and multi-physics problems; and
4. Design of physical and computational experiments;
However, constructing accurate surrogates for such problems and computing their predictions along with the uncertainties they introduce, constitute additional challenges. This workshop will explore a variety of approaches that have been developed to address such challenges, including Gaussian processes, sparse interpolation and projection, discrete least squares, compressed sensing, dimension reduction, multi-fidelity formulations, Bayesian inference, homogenization techniques, and atomistic to continuum coupling methods.
In addition to invited talks, a poster session will be organised, as well as a two panel discussions.
Please see the workshop webpage for a list of speakers and tentative titles, and for registration details.
This workshop is the second event in a six-month programme on Uncertainty Quantification at the Isaac Newton Institute, see:
https://www.newton.ac.uk/event/unq
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Organisers
Serge Guillas, University College London, UK
Lindsay Lee, University of Leeds, UK
Fabio Nobile, EPFL, Switzerland
Clayton Webster, Oak Ridge National Labs, USA
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