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Conditional Karhunen–Loève regression model with Basis Adaptation for high-dimensional problems: Uncertainty quantification and inverse modeling
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Conditional Karhunen–Loève regression model with Basis Adaptation for high-dimensional problems: Uncertainty quantification and inverse modeling (2023)Conditional Karhunen–Loève regression mod…Accelerated basis adaptation in homogeneous chaos spaces (2021)Accelerated basis adaptation …Surrogate modeling of high-dimensional problems via data-driven polynomial chaos expansions and sparse partial least square (2020)Surrogate modeling of high-di…Conditional Karhunen-Loève expansion for uncertainty quantification and active learning in partial differential equation models (2020)Conditional Karhunen-Loève ex…Stochastic Basis Adaptation and Spatial Domain Decomposition for Partial Differential Equations with Random Coefficients (2018)Stochastic Basis Adaptation a…Polynomial chaos expansion for surrogate modelling: Theory and software (2018)Polynomial chaos expansion fo…Inverse regression-based uncertainty quantification algorithms for high-dimensional models: Theory and practice (2016)Inverse regression-based unce…Convergence study of the truncated Karhunen–Loeve expansion for simulation of stochastic processes (2001)Convergence study of the trun…Random Fields: Analysis and Synthesis (1983)Simulation of Stochastic Processes by Spectral Representation (1991)Stochastic Finite Elements: A Spectral Approach (1991)Implementation of Karhunen–Loeve expansion for simulation using a wavelet-Galerkin scheme (2002)Numerical methods for the discretization of random fields by means of the Karhunen–Loève expansion (2014)Random function based spectral representation of stationary and non-stationary stochastic processes (2016)Simulation Modeling and Analysis. (1983)Design and Analysis of Computer Experiments (1989)Efficient evaluation of small failure probability in high‐dimensional groundwater contaminant transport modeling via a two‐stage M onte C arlo method (2017)Active learning with generalized sliced inverse regression for high-dimensional reliability analysis (2021)Estimation of small failure probability using generalized subset simulation (2021)The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data (2008)A non-adapted sparse approximation of PDEs with stochastic inputs (2011)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (1979)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)Safety analysis and reliability assessment of engineering structures – The success story of SARA (2019)Efficient structural reliability analysis by using a PGD model in an adaptive importance sampling schema (2020)Optimization of a higher-order sandwich composite beam under uncertainties (2021)A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data (2010)GAUSSIAN PROCESS REGRESSION AND CONDITIONAL KARHUNEN-LOÈVE EXPANSION FOR FORWARD UNCERTAINTY QUANTIFICATION AND INVERSE MODELING IN THE PRESENCE OF MEASUREMENT NOISE (2022)Uncertainty analysis of simplified 1D and 2D shallow water equations via the Karhunen–Loéve expansion and Monte Carlo simulations (2023)Global Sensitivity Analysis. The Primer (2007)A unified approach for global sensitivity analysis based on active subspace and Kriging (2021)An overview on uncertainty quantification and probabilistic learning on manifolds in multiscale mechanics of materials (2023)Partial least squares-based polynomial chaos Kriging for high-dimensional reliability analysis (2023)Modeling uncertainty in flow simulations via generalized polynomial chaos (2003)Consideration of multi-variable uncertainty using the GPC method for the dynamic study of a two-stage gearbox of a wind turbine (2022)Multifidelity uncertainty quantification with models based on dissimilar parameters (2023)Data-Driven Projection Pursuit Adaptation of Polynomial Chaos Expansions for Dependent High-Dimensional Parameters (2024)
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References

  • 2001Convergence study of the truncated Karhunen–Loeve expansion for simulation of stochastic processes466 cited
  • 2020Surrogate modeling of high-dimensional problems via data-driven polynomial chaos expansions and sparse partial least square55 cited
  • 2016Inverse regression-based uncertainty quantification algorithms for high-dimensional models: Theory and practice51 cited
  • 2018Polynomial chaos expansion for surrogate modelling: Theory and software42 cited
  • 2021Accelerated basis adaptation in homogeneous chaos spaces26 cited
  • 2020Conditional Karhunen-Loève expansion for uncertainty quantification and active learning in partial differential equation models21 cited
  • 2018Stochastic Basis Adaptation and Spatial Domain Decomposition for Partial Differential Equations with Random Coefficients7 cited

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