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Fast estimation of expected information gains for Bayesian experimental designs based on Laplace approximations
14 references·16 citing·34 second hop
Fast estimation of expected information gains for Bayesian experimental designs based on Laplace approximations (2013)Fast estimation of expected information g…Simulation-based optimal Bayesian experimental design for nonlinear systems (2012)Simulation-based optimal Baye…ON THE OPTIMAL POLYNOMIAL APPROXIMATION OF STOCHASTIC PDES BY GALERKIN AND COLLOCATION METHODS (2012)ON THE OPTIMAL POLYNOMIAL APP…Stochastic Spectral Galerkin and Collocation Methods for PDEs with Random Coefficients: A Numerical Comparison (2010)Stochastic Spectral Galerkin …Optimum Experimental Designs, With SAS (2008)Optimum Experimental Designs,…A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data (2008)A Sparse Grid Stochastic Coll…Optimum Experimental Designs, with SAS (2007)Optimum Experimental Designs,…A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data (2007)A Stochastic Collocation Meth…Optimal Design of Experiments (2006)Optimal Design of ExperimentsEstimating Expected Information Gains for Experimental Designs With Application to the Random Fatigue-Limit Model (2003)Estimating Expected Informati…Bayesian Experimental Design: A Review (1995)Bayesian Experimental Design:…Optimum Experimental Designs (1993)Optimum Experimental DesignsOptimal design of experiments (1993)Optimal design of experimentsRecent Advances in Nonlinear Experimental Design (1989)Recent Advances in Nonlinear …DESIGN OF EXPERIMENTS IN NON-LINEAR SITUATIONS (1959)DESIGN OF EXPERIMENTS IN NON-…Modern Bayesian Experimental Design (2024)Modern Bayesian Experimental …Optimal experimental design for infinite-dimensional Bayesian inverse problems governed by PDEs: a review (2021)Optimal experimental design f…Multilevel Monte Carlo estimation of expected information gains (2019)Multilevel Monte Carlo estima…Fast uncertainty quantification for dynamic flux balance analysis using non-smooth polynomial chaos expansions (2019)Fast uncertainty quantificati…A second order SAP algorithm for risk and reliability based design optimization (2019)A second order SAP algorithm …Goal-oriented optimal design of experiments for large-scale Bayesian linear inverse problems (2018)Goal-oriented optimal design …Fast Bayesian experimental design: Laplace-based importance sampling for the expected information gain (2018)Fast Bayesian experimental de…Efficient D-Optimal Design of Experiments for Infinite-Dimensional Bayesian Linear Inverse Problems (2018)Efficient D-Optimal Design of…Principles of Experimental Design for Big Data Analysis (2017)Principles of Experimental De…Efficient Bayesian Experimentation Using an Expected Information Gain Lower Bound (2017)Efficient Bayesian Experiment…Calibration experimental design considering field response and model uncertainty (2017)Calibration experimental desi…A gradient-based polynomial chaos approach for risk and reliability-based design optimization (2017)A gradient-based polynomial c…Sequential Bayesian optimal experimental design via approximate dynamic programming (2016)Sequential Bayesian optimal e…Gaussian process surrogates for failure detection: A Bayesian experimental design approach (2016)Gaussian process surrogates f…Fully Bayesian Experimental Design for Pharmacokinetic Studies (2015)Fully Bayesian Experimental D…Fast Bayesian optimal experimental design for seismic source inversion (2015)Fast Bayesian optimal experim…The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)High-Order Collocation Methods for Differential Equations with Random Inputs (2005)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)Applied Statistical Decision Theory (1962)Theory of optimal experiments (1972)Design and Analysis of Computer Experiments (1989)Kriging metamodeling in simulation: A review (2007)Response surface methodology (2010)Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting (2012)Stochastic Finite Elements: A Spectral Approach (1991)Multivariate stochastic approximation using a simultaneous perturbation gradient approximation (1992)Adaptive Smolyak Pseudospectral Approximations (2013)A Review of Modern Computational Algorithms for Bayesian Optimal Design (2015)Engineering Design with Digital Thread (2018)Design of Experiments (1936)Theory of Optimal Experiments. (1972)Optimum Experimental Designs for Properties of a Compartmental Model (1993)Fast Computation of Designs Robust to Parameter Uncertainty for Nonlinear Settings (2009)GRADIENT-BASED STOCHASTIC OPTIMIZATION METHODS IN BAYESIAN EXPERIMENTAL DESIGN (2014)Response surface design evaluation and comparison (2008)Least squares polynomial chaos expansion: A review of sampling strategies (2017)Uncertainty Quantification and Polynomial Chaos Techniques in Computational Fluid Dynamics (2008)DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. Version 5.0, user's manual. (2010)A Basis for the Selection of a Response Surface Design (1959)Response Surface Methodology: 1966-1988 (1989)Designing Environmental Field Studies (1991)Uniform Design: Theory and Application (2000)State-of-the-Art Review: A User’s Guide to the Brave New World of Designing Simulation Experiments (2005)Making and Evaluating Point Forecasts (2011)Response Surface Methodology: A Retrospective and Literature Survey (2004)Global sensitivity analysis using polynomial chaos expansions (2007)Design of experiments applications in bioprocessing: Concepts and approach (2013)Sparse polynomial chaos expansions via compressed sensing and D-optimal design (2018)
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References

  • 1995Bayesian Experimental Design: A Review1,846 cited
  • 1993Optimal design of experiments1,539 cited
  • 1993Optimum Experimental Designs1,447 cited
  • 2007A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data1,396 cited
  • 2007Optimum Experimental Designs, with SAS1,268 cited
  • 2008A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data942 cited
  • 1959DESIGN OF EXPERIMENTS IN NON-LINEAR SITUATIONS738 cited
  • 2006Optimal Design of Experiments684 cited
  • 2012Simulation-based optimal Bayesian experimental design for nonlinear systems451 cited
  • 1989Recent Advances in Nonlinear Experimental Design259 cited
  • 2010Stochastic Spectral Galerkin and Collocation Methods for PDEs with Random Coefficients: A Numerical Comparison176 cited
  • 2003Estimating Expected Information Gains for Experimental Designs With Application to the Random Fatigue-Limit Model169 cited
  • 2008Optimum Experimental Designs, With SAS165 cited
  • 2012ON THE OPTIMAL POLYNOMIAL APPROXIMATION OF STOCHASTIC PDES BY GALERKIN AND COLLOCATION METHODS136 cited

Cited by

  • 2024Modern Bayesian Experimental Design

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110 cited
  • 2021Optimal experimental design for infinite-dimensional Bayesian inverse problems governed by PDEs: a review85 cited
  • 2018Fast Bayesian experimental design: Laplace-based importance sampling for the expected information gain78 cited
  • 2018Goal-oriented optimal design of experiments for large-scale Bayesian linear inverse problems59 cited
  • 2018Efficient D-Optimal Design of Experiments for Infinite-Dimensional Bayesian Linear Inverse Problems50 cited
  • 2017Calibration experimental design considering field response and model uncertainty46 cited
  • 2015Fast Bayesian optimal experimental design for seismic source inversion46 cited
  • 2017Principles of Experimental Design for Big Data Analysis45 cited
  • 2017Efficient Bayesian Experimentation Using an Expected Information Gain Lower Bound44 cited
  • 2016Sequential Bayesian optimal experimental design via approximate dynamic programming41 cited
  • 2015Fully Bayesian Experimental Design for Pharmacokinetic Studies40 cited
  • 2016Gaussian process surrogates for failure detection: A Bayesian experimental design approach32 cited
  • 2019Multilevel Monte Carlo estimation of expected information gains28 cited
  • 2019Fast uncertainty quantification for dynamic flux balance analysis using non-smooth polynomial chaos expansions26 cited
  • 2019A second order SAP algorithm for risk and reliability based design optimization24 cited
  • 2017A gradient-based polynomial chaos approach for risk and reliability-based design optimization23 cited