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Stochastic reduced order models for inverse problems under uncertainty
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Stochastic reduced order models for inverse problems under uncertainty (2014)Stochastic reduced order models for inver…A Trust-Region Algorithm with Adaptive Stochastic Collocation for PDE Optimization under Uncertainty (2013)A Trust-Region Algorithm with…Stochastic reduced order models for random vectors: Application to random eigenvalue problems (2012)Stochastic reduced order mode…A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data (2010)A Stochastic Collocation Meth…A Stochastic Collocation Approach to Bayesian Inference in Inverse Problems (2009)A Stochastic Collocation Appr…A scalable framework for the solution of stochastic inverse problems using a sparse grid collocation approach (2008)A scalable framework for the …Reduced order models for random functions. Application to stochastic problems (2007)Reduced order models for rand…A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data (2007)A Stochastic Collocation Meth…High-Order Collocation Methods for Differential Equations with Random Inputs (2005)High-Order Collocation Method…Stochastic inverse heat conduction using a spectral approach (2004)Stochastic inverse heat condu…The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)The Wiener--Askey Polynomial …Stochastic Finite Elements: A Spectral Approach (1991)Stochastic Finite Elements: A…Ingredients for a general purpose stochastic finite elements implementation (1999)Modeling uncertainty in flow simulations via generalized polynomial chaos (2003)Uncertainty propagation in finite deformations––A spectral stochastic Lagrangian approach (2005)Application of Stochastic Finite Element Methods to Study the Sensitivity of ECG Forward Modeling to Organ Conductivity (2007)Identification of composite uncertain material parameters from experimental modal data (2014)Interpolation of Spatial Data: Some Theory for Kriging (2000)Lectures on Stochastic Programming: Modeling and Theory (2009)Inexact Objective Function Evaluations in a Trust-Region Algorithm for PDE-Constrained Optimization under Uncertainty (2014)Risk-Averse PDE-Constrained Optimization Using the Conditional Value-At-Risk (2016)Mean-Variance Risk-Averse Optimal Control of Systems Governed by PDEs with Random Parameter Fields Using Quadratic Approximations (2017)Applied non-Gaussian processes : examples, theory, simulation, linear random vibration, and MATLAB solutions (1995)Galerkin Finite Element Approximations of Stochastic Elliptic Partial Differential Equations (2004)Uncertainty Quantification of Crosstalk Using Stochastic Reduced Order Models (2016)UQpy: A general purpose Python package and development environment for uncertainty quantification (2020)Large Sample Properties of Simulations Using Latin Hypercube Sampling (1987)Global sensitivity analysis using polynomial chaos expansions (2007)AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation (2011)A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data (2008)An adaptive algorithm to build up sparse polynomial chaos expansions for stochastic finite element analysis (2009)Survey of Multifidelity Methods in Uncertainty Propagation, Inference, and Optimization (2018)Identification of high-dimension polynomial chaos expansions with random coefficients for non-Gaussian tensor-valued random fields using partial and limited experimental data (2010)A computational inverse method for identification of non-Gaussian random fields using the Bayesian approach in very high dimension (2011)Optimal control with stochastic PDE constraints and uncertain controls (2011)Adaptive sparse polynomial chaos expansion based on least angle regression (2010)Simulation-based optimal Bayesian experimental design for nonlinear systems (2012)GRADIENT-BASED STOCHASTIC OPTIMIZATION METHODS IN BAYESIAN EXPERIMENTAL DESIGN (2014)Stochastic finite element methods for partial differential equations with random input data (2014)Recent Developments in Spectral Stochastic Methods for the Numerical Solution of Stochastic Partial Differential Equations (2009)An adaptive high-dimensional stochastic model representation technique for the solution of stochastic partial differential equations (2010)Multi-level Monte Carlo Finite Element method for elliptic PDEs with stochastic coefficients (2011)
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References

  • 1991Stochastic Finite Elements: A Spectral Approach5,753 cited
  • 2002The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations4,821 cited
  • 2005High-Order Collocation Methods for Differential Equations with Random Inputs1,522 cited
  • 2007A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data1,396 cited
  • 2010A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data400 cited
  • 2009A Stochastic Collocation Approach to Bayesian Inference in Inverse Problems285 cited
  • 2013A Trust-Region Algorithm with Adaptive Stochastic Collocation for PDE Optimization under Uncertainty113 cited
  • 2007Reduced order models for random functions. Application to stochastic problems94 cited
  • 2008A scalable framework for the solution of stochastic inverse problems using a sparse grid collocation approach91 cited
  • 2004Stochastic inverse heat conduction using a spectral approach83 cited
  • 2012Stochastic reduced order models for random vectors: Application to random eigenvalue problems52 cited

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