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Towards efficient uncertainty quantification in complex and large-scale biomechanical problems based on a Bayesian multi-fidelity scheme
16 references·13 citing·31 second hop
Towards efficient uncertainty quantification in complex and large-scale biomechanical problems based on a Bayesian multi-fidelity scheme (2014)Towards efficient uncertainty quantificat…Multilevel Monte Carlo methods and applications to elliptic PDEs with random coefficients (2011)Multilevel Monte Carlo method…A simple and efficient methodology to approximate a general non-Gaussian stationary stochastic process by a translation process (2011)A simple and efficient method…Numerical Methods for Stochastic Computations: A Spectral Method Approach (2010)Numerical Methods for Stochas…A Stochastic Collocation Method for Uncertainty Quantification and Propagation in Cardiovascular Simulations (2010)A Stochastic Collocation Meth…Recent Advances in Non-Intrusive Polynomial Chaos and Stochastic Collocation Methods for Uncertainty Analysis and Design (2009)Recent Advances in Non-Intrus…Fast Numerical Methods for Stochastic Computations: A Review (2009)Fast Numerical Methods for St…The stochastic finite element method: Past, present and future (2008)The stochastic finite element…Application of line sampling simulation method to reliability benchmark problems (2006)Application of line sampling …Latin Hypercube Sampling for Stochastic Finite Element Analysis (2002)Latin Hypercube Sampling for …Estimation of small failure probabilities in high dimensions by subset simulation (2001)Estimation of small failure p…A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)A Comparison of Three Methods…Monte Carlo Treatment of Random Fields: A Broad Perspective (1998)Monte Carlo Treatment of Rand…Monte Carlo techniques in computational stochastic mechanics (1998)Monte Carlo techniques in com…Simulation of Multi-Dimensional Gaussian Stochastic Fields by Spectral Representation (1996)Simulation of Multi-Dimension…Stochastic Finite Elements: A Spectral Approach (1991)Stochastic Finite Elements: A…Digital simulation of random processes and its applications (1972)Digital simulation of random …A multi-fidelity stochastic simulation scheme for estimation of small failure probabilities (2023)A multi-fidelity stochastic s…Surrogate‐based Bayesian calibration of biomechanical models with isotropic material behavior (2022)Surrogate‐based Bayesian cali…A generalized probabilistic learning approach for multi-fidelity uncertainty quantification in complex physical simulations (2022)A generalized probabilistic l…A maximum cost-performance sampling strategy for multi-fidelity PC-Kriging (2021)A maximum cost-performance sa…The effects of clinically‐derived parametric data uncertainty in patient‐specific coronary simulations with deformable walls (2020)The effects of clinically‐der…Multi-fidelity response surfaces for uncertainty quantification in beams using coarse and fine finite element discretizations (2020)Multi-fidelity response surfa…Fast uncertainty quantification of tracer distribution in the brain interstitial fluid with multilevel and quasi Monte Carlo (2020)Fast uncertainty quantificati…Towards efficient uncertainty quantification with high-resolution morphodynamic models: A multifidelity approach applied to channel sedimentation (2019)Towards efficient uncertainty…Multifidelity approaches for uncertainty quantification (2019)Multifidelity approaches for …Multi-fidelity uncertainty quantification method with application to nonlinear structural response analysis (2019)Multi-fidelity uncertainty qu…High-dimensional and higher-order multifidelity Monte Carlo estimators (2019)High-dimensional and higher-o…Efficient Possibilistic Uncertainty Analysis of a Car Crash Scenario Using a Multifidelity Approach (2019)Efficient Possibilistic Uncer…Uncertainty quantification of simulated biomechanical stimuli in coronary artery bypass grafts (2018)Uncertainty quantification of…Simulation and the Monte Carlo Method (1981)A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models (2012)The generalization of Latin hypercube sampling (2015)Simulation and the Monte Carlo Method (2016)Structural reliability under combined random load sequences (1978)The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)Global sensitivity analysis using polynomial chaos expansions (2007)Comparison of Non-Intrusive Polynomial Chaos and Stochastic Collocation Methods for Uncertainty Quantification (2009)Mixed aleatory-epistemic uncertainty quantification with stochastic expansions and optimization-based interval estimation (2011)First order reliability method for time-variant problems using series expansions (2014)Spectral Methods for Uncertainty Quantification (2010)Further analysis of multilevel Monte Carlo methods for elliptic PDEs with random coefficients (2013)Optimal Model Management for Multifidelity Monte Carlo Estimation (2016)Large Sample Properties of Simulations Using Latin Hypercube Sampling 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analyses of complex systems (2003)Simulation of Ergodic Multivariate Stochastic Processes (1996)An Introduction to Computational Stochastic PDEs (2014)Numerical methods for the discretization of random fields by means of the Karhunen–Loève expansion (2014)Direct probability integral method for stochastic response analysis of static and dynamic structural systems (2019)Recent Trends in the Modeling and Quantification of Non-probabilistic Uncertainty (2019)
this work references cited by second hop

References

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  • 2011A simple and efficient methodology to approximate a general non-Gaussian stationary stochastic process by a translation process168 cited
  • 2010A Stochastic Collocation Method for Uncertainty Quantification and Propagation in Cardiovascular Simulations146 cited
  • Cited by

    • 2020The effects of clinically‐derived parametric data uncertainty in patient‐specific coronary simulations with deformable walls44 cited
    • 2018Uncertainty quantification of simulated biomechanical stimuli in coronary artery bypass grafts37 cited
    • 2022A generalized probabilistic learning approach for multi-fidelity uncertainty quantification in complex physical simulations22 cited
    • 2019Multifidelity approaches for uncertainty quantification15 cited
    • 2023A multi-fidelity stochastic simulation scheme for estimation of small failure probabilities13 cited
    • 2019High-dimensional and higher-order multifidelity Monte Carlo estimators13 cited
    • 2020Fast uncertainty quantification of tracer distribution in the brain interstitial fluid with multilevel and quasi Monte Carlo12 cited
    • 2022Surrogate‐based Bayesian calibration of biomechanical models with isotropic material behavior12 cited
    • 2019Towards efficient uncertainty quantification with high-resolution morphodynamic models: A multifidelity approach applied to channel sedimentation11 cited
    • 2021A maximum cost-performance sampling strategy for multi-fidelity PC-Kriging8 cited
    • 2020Multi-fidelity response surfaces for uncertainty quantification in beams using coarse and fine finite element discretizations8 cited
    • 2019Multi-fidelity uncertainty quantification method with application to nonlinear structural response analysis7 cited
    • 2019Efficient Possibilistic Uncertainty Analysis of a Car Crash Scenario Using a Multifidelity Approach7 cited