QUIET 2017 - Quantification of Uncertainty: Improving Efficiency and Technology

Speaker List

• Francesco Ballarin
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    Weighted reduced order methods for parametrized PDEs with random inputs

• Simone Brugiapaglia
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    Recent advances in compressed sensing techniques for the numerical approximation of PDEs

• Peng Chen
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    Hessian-based sampling for goal-oriented model reduction

• Nicholas Dexter
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    Compressed sensing reconstruction of Hilbert-valued solutions to parametrized PDEs

• Howard Elman Elman
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    Collocation Methods for Exploring Perturbations in Linear Stability Analysis

• Jochen Garcke
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    Operator based multi-scale analysis of simulation bundles

• Jean-Frédéric Gerbeau
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    Modeling variability in cardiac electrophysiology

• Michael Griebel
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    Sparse Grid Methods in Uncertainty Quantification

• Jan Hesthaven
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    Structure Preserving Reduced Order Models

• Jens Lang
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    Reduced-order models with space-adapted snapshots

• Ivon Maday (Laboratoire Jacques-Louis Lions, Université Pierre et Marie Curie)
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    Stabilization of EIM and PBDW Methods with Noisy Observations

• Laura Mainini
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    Model order reduction for real time decisions from incomplete and uncertain measurements

• Herman G. Matthies
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    Conditional Expectation as the Basis of Bayesian Updating

• Giovanni Migliorati
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    Multivariate approximation in downward closed polynomial spaces

• Olga Mula
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    Dictionary measurement selection for state estimation with reduced basis

• Fabio Nobile
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    Multi-Index polynomial chaos methods for random PDEs

• Sarah Osborn
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    Scalable Hierarchical Sampling of Gaussian Random Fields for Large-Scale Multilevel Monte Carlo Simulations

• Benjamin Peherstorfer
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    Multifidelity methods for uncertainty propagation and rare event simulation

• Eric T. Phipps
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    Improving Sampling-based Uncertainty Quantification Performance Through Embedded Ensemble Propagation

• Catherine Powell
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    An Efficient Reduced Basis Solver for Stochastic Galerkin Matrix Equations

• Clémentine Prieur
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    Goal-oriented error estimation for fast approximations of nonlinear problems

• Francesco Rizzi
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    Tackling UQ in DARMA, a Programming Model for Task-Based Execution at Extreme-Scale

• Maria Vittoria Salvetti
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    Stochastic sensitivity analysis to grid resolution and closure modeling in large-eddy simulation

• Pablo Seleson
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    Uncertainty Quantification in Materials Modeling

• Ralph C. Smith
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    Sensitivity Analysis and Active Subspace Construction for Surrogate Models Employed for Bayesian Inference

• Bedřich Sousedík
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    Spectral stochastic finite elements for two nonlinear problems

• Lorenzo Tamellini
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    Sparse grid approximation of elliptic PDEs with lognormal diffusion coefficient

• Elisabeth Ullmann Ullmann
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    Multilevel Sequential Monte Carlo for Bayesian Inverse Problems

• Clayton G. Webster
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    Sparse approximation of high-dimensional functions via convex and nonconvex regularizations

• Larry Winter
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    It's Really Dark Down There: UQ in Groundwater Hydrology

• Peter Zaspel
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    Scalable solvers for meshless methods on many-core clusters