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Inverse regression-based uncertainty quantification algorithms for high-dimensional models: Theory and practice
14 references·14 citing·31 second hop
Inverse regression-based uncertainty quantification algorithms for high-dimensional models: Theory and practice (2016)Inverse regression-based uncertainty quan…Active Subspace Methods in Theory and Practice: Applications to Kriging Surfaces (2014)Active Subspace Methods in Th…Adaptive ANOVA decomposition of stochastic incompressible and compressible flows (2011)Adaptive ANOVA decomposition …Uncertainty quantification with experimental data and complex system models (2010)Uncertainty quantification wi…Multi-element probabilistic collocation method in high dimensions (2009)Multi-element probabilistic c…An Anisotropic Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data (2008)An Anisotropic Sparse Grid St…A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data (2008)A Sparse Grid Stochastic Coll…Sparse grid collocation schemes for stochastic natural convection problems (2007)Sparse grid collocation schem…A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data (2007)A Stochastic Collocation Meth…Modeling uncertainty in flow simulations via generalized polynomial chaos (2003)Modeling uncertainty in flow …Simulation modeling and analysis (1999)Simulation modeling and analy…Stochastic Response Surface Methods (SRSMs) for Uncertainty Propagation: Application to Environmental and Biological Systems (1998)Stochastic Response Surface M…Stochastic Finite Elements: A Spectral Approach (1991)Stochastic Finite Elements: A…Design and Analysis of Computer Experiments (1989)Design and Analysis of Comput…Simulation Modeling and Analysis. (1983)Simulation Modeling and Analy…Uncertainty quantification in low-probability response estimation using sliced inverse regression and polynomial chaos expansion (2023)Uncertainty quantification in…Sparse moment quadrature for uncertainty modeling and quantification (2023)Sparse moment quadrature for …Conditional Karhunen–Loève regression model with Basis Adaptation for high-dimensional problems: Uncertainty quantification and inverse modeling (2023)Conditional Karhunen–Loève re…High-Dimensional Reliability Method Accounting for Important and Unimportant Input Variables (2021)High-Dimensional Reliability …Estimation of small failure probability using generalized subset simulation (2021)Estimation of small failure p…Active learning with generalized sliced inverse regression for high-dimensional reliability analysis (2021)Active learning with generali…A Polymorphic Polynomial Chaos Formulation for Mixed Epistemic-Aleatory Uncertainty Quantification of RF/Microwave Circuits (2021)A Polymorphic Polynomial Chao…Conditional Karhunen-Loève expansion for uncertainty quantification and active learning in partial differential equation models (2020)Conditional Karhunen-Loève ex…An efficient and robust adaptive sampling method for polynomial chaos expansion in sparse Bayesian learning framework (2019)An efficient and robust adapt…A Predictor–Corrector Algorithm for Fast Polynomial Chaos-Based Uncertainty Quantification of Multi-Walled Carbon Nanotube Interconnects (2019)A Predictor–Corrector Algorit…Sliced-Inverse-Regression--Aided Rotated Compressive Sensing Method for Uncertainty Quantification (2018)Sliced-Inverse-Regression--Ai…Reduced Dimensional Chebyshev-Polynomial Chaos Approach for Fast Mixed Epistemic-Aleatory Uncertainty Quantification of Transmission Line Networks (2018)Reduced Dimensional Chebyshev…Efficient evaluation of small failure probability in high‐dimensional groundwater contaminant transport modeling via a two‐stage M onte C arlo method (2017)Efficient evaluation of small…A two-stage adaptive stochastic collocation method on nested sparse grids for multiphase flow in randomly heterogeneous porous media (2016)A two-stage adaptive stochast…Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)High-Order Collocation Methods for Differential Equations with Random Inputs (2005)An adaptive hierarchical sparse grid collocation algorithm for the solution of stochastic differential equations (2009)A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data (2010)A non-adapted sparse approximation of PDEs with stochastic inputs (2011)The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)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)Statistics for Experimenters: An Introduction to Design, Data Analysis and Model Building. (1979)Empirical Model Building and Response Surfaces (1988)Uncertainty quantification in reacting-flow simulations through non-intrusive spectral projection (2003)Probabilistic collocation method for flow in porous media: Comparisons with other stochastic methods (2007)A Chebyshev interval method for nonlinear dynamic systems under uncertainty (2012)Design of Experiments (1936)On a Measure of the Information Provided by an Experiment (1956)Minimax and maximin distance designs (1990)Variance based sensitivity analysis of model output. 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(2010)An adaptive multi-element generalized polynomial chaos method for stochastic differential equations (2005)Fast Numerical Methods for Stochastic Computations: A Review (2009)Testing ecological models: the meaning of validation (1996)Kriging Metamodeling in Simulation: A Review (2007)Verification and validation of simulation models (2012)Modeling Good Research Practices—Overview: A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force-1 (2012)
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Cited by

  • 2021Active learning with generalized sliced inverse regression for high-dimensional reliability analysis48 cited
  • 2021Estimation of small failure probability using generalized subset simulation45 cited
  • 2017Efficient evaluation of small failure probability in high‐dimensional groundwater contaminant transport modeling via a two‐stage M onte C arlo method34 cited
  • 2019An efficient and robust adaptive sampling method for polynomial chaos expansion in sparse Bayesian learning framework34 cited
  • 2023Uncertainty quantification in low-probability response estimation using sliced inverse regression and polynomial chaos expansion29 cited
  • 2018Reduced Dimensional Chebyshev-Polynomial Chaos Approach for Fast Mixed Epistemic-Aleatory Uncertainty Quantification of Transmission Line Networks23 cited
  • 2021High-Dimensional Reliability Method Accounting for Important and Unimportant Input Variables23 cited
  • 2016A two-stage adaptive stochastic collocation method on nested sparse grids for multiphase flow in randomly heterogeneous porous media22 cited
  • 2020Conditional Karhunen-Loève expansion for uncertainty quantification and active learning in partial differential equation models21 cited
  • 2019A Predictor–Corrector Algorithm for Fast Polynomial Chaos-Based Uncertainty Quantification of Multi-Walled Carbon Nanotube Interconnects16 cited
  • 2021A Polymorphic Polynomial Chaos Formulation for Mixed Epistemic-Aleatory Uncertainty Quantification of RF/Microwave Circuits12 cited
  • 2023Sparse moment quadrature for uncertainty modeling and quantification12 cited
  • 2023Conditional Karhunen–Loève regression model with Basis Adaptation for high-dimensional problems: Uncertainty quantification and inverse modeling6 cited
  • 2018Sliced-Inverse-Regression--Aided Rotated Compressive Sensing Method for Uncertainty Quantification6 cited