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GRADIENT-BASED STOCHASTIC OPTIMIZATION METHODS IN BAYESIAN EXPERIMENTAL DESIGN
16 references·16 citing·28 second hopsampled
GRADIENT-BASED STOCHASTIC OPTIMIZATION METHODS IN BAYESIAN EXPERIMENTAL DESIGN (2014)GRADIENT-BASED STOCHASTIC OPTIMIZATION ME…Spectral methods for uncertainty quantification : with applications to computational fluid dynamics (2010)Spectral methods for uncertai…Fast Numerical Methods for Stochastic Computations: A Review (2009)Fast Numerical Methods for St…Uncertainty Quantification and Polynomial Chaos Techniques in Computational Fluid Dynamics (2008)Uncertainty Quantification an…Stochastic Simulation (2007)Stochastic SimulationStochastic Approximation and Recursive Algorithms and Applications (2003)Stochastic Approximation and …The Sample Average Approximation Method for Stochastic Discrete Optimization (2002)The Sample Average Approximat…Monte Carlo bounding techniques for determining solution quality in stochastic programs (1999)Monte Carlo bounding techniqu…Bayesian Experimental Design: A Review (1995)Bayesian Experimental Design:…Optimum Experimental Designs (1993)Optimum Experimental DesignsAcceleration of Stochastic Approximation by Averaging (1992)Acceleration of Stochastic Ap…Stochastic Finite Elements: A Spectral Approach (1991)Stochastic Finite Elements: A…Gradient Estimation via Perturbation Analysis (1991)Gradient Estimation via Pertu…DESIGN OF EXPERIMENTS IN NON-LINEAR SITUATIONS (1959)DESIGN OF EXPERIMENTS IN NON-…On a Measure of the Information Provided by an Experiment (1956)On a Measure of the Informati…Stochastic Estimation of the Maximum of a Regression Function (1952)Stochastic Estimation of the …A Stochastic Approximation Method (1951)A Stochastic Approximation Me…Modern Bayesian Experimental Design (2024)Modern Bayesian Experimental …A Fast and Scalable Computational Framework for Large-Scale High-Dimensional Bayesian Optimal Experimental Design (2023)A Fast and Scalable Computati…Surrogate-based sequential Bayesian experimental design using non-stationary Gaussian Processes (2021)Surrogate-based sequential Ba…Optimal experimental design for infinite-dimensional Bayesian inverse problems governed by PDEs: a review (2021)Optimal experimental design f…Optimal design of experiments for optimization-based model calibration using Fisher information matrix (2021)Optimal design of experiments…Output-weighted optimal sampling for Bayesian regression and rare event statistics using few samples (2020)Output-weighted optimal sampl…Nesterov-aided stochastic gradient methods using Laplace approximation for Bayesian design optimization (2020)Nesterov-aided stochastic gra…Simulation and Sensor Optimization for Multifidelity Dynamics Model Calibration (2019)Simulation and Sensor Optimiz…Goal-oriented optimal design of experiments for large-scale Bayesian linear inverse problems (2018)Goal-oriented optimal design …Efficient D-Optimal Design of Experiments for Infinite-Dimensional Bayesian Linear Inverse Problems (2018)Efficient D-Optimal Design of…Bayesian adaptation of chaos representations using variational inference and sampling on geodesics (2018)Bayesian adaptation of chaos …Sensor placement for calibration of spatially varying model parameters (2017)Sensor placement for calibrat…Efficient Bayesian Experimentation Using an Expected Information Gain Lower Bound (2017)Efficient Bayesian Experiment…Sequential Bayesian optimal experimental design via approximate dynamic programming (2016)Sequential Bayesian optimal e…Variational Bayesian strategies for high-dimensional, stochastic design problems (2015)Variational Bayesian strategi…Fully Bayesian Experimental Design for Pharmacokinetic Studies (2015)Fully Bayesian Experimental D…A stochastic programming approach for supply chain network design under uncertainty (2004)Convex Approximations of Chance Constrained Programs (2006)Lectures on Stochastic Programming: Modeling and Theory (2009)Introduction to Stochastic Programming (2011)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)Proceedings of the 2002 Winter Simulation Conference (2002)Computational methods in optimization considering uncertainties – An overview (2008)A unified framework for stochastic optimization (2018)The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations (2002)Global sensitivity analysis using polynomial chaos expansions (2007)AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation (2011)Some aspects of the sequential design of experiments (1952)mirt : A Multidimensional Item Response Theory Package for the R Environment (2012)Multivariate stochastic approximation using a simultaneous perturbation gradient approximation (1992)Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems (2012)Maximum entropy sampling (1987)The Stag Hunt and the Evolution of Social Structure (2003)Signals (2010)Optimization of computer simulation models with rare events (1997)Optimal design of experiments (1993)Response Surface Methodology: A Retrospective and Literature Survey (2004)A Guide to Sample Average Approximation (2014)Simulation Modeling and Analysis (2016)
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References

  • 1951A Stochastic Approximation Method9,630 cited
  • 1991Stochastic Finite Elements: A Spectral Approach5,753 cited
  • 1952Stochastic Estimation of the Maximum of a Regression Function2,134 cited
  • 2002The Sample Average Approximation Method for Stochastic Discrete Optimization1,989 cited
  • 1995Bayesian Experimental Design: A Review1,846 cited
  • 2003Stochastic Approximation and Recursive Algorithms and Applications1,845 cited
  • 1992Acceleration of Stochastic Approximation by Averaging1,822 cited
  • 1956On a Measure of the Information Provided by an Experiment1,507 cited
  • 1993Optimum Experimental Designs1,447 cited
  • 2007Stochastic Simulation1,121 cited
  • 2008Uncertainty Quantification and Polynomial Chaos Techniques in Computational Fluid Dynamics769 cited
  • 1959DESIGN OF EXPERIMENTS IN NON-LINEAR SITUATIONS738 cited
  • 1991Gradient Estimation via Perturbation Analysis707 cited
  • 1999Monte Carlo bounding techniques for determining solution quality in stochastic programs705 cited
  • 2009Fast Numerical Methods for Stochastic Computations: A Review608 cited
  • 2010

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Spectral methods for uncertainty quantification : with applications to computational fluid dynamics
572 cited

Cited by

  • 2024Modern Bayesian Experimental Design110 cited
  • 2021Optimal experimental design for infinite-dimensional Bayesian inverse problems governed by PDEs: a review85 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
  • 2020Output-weighted optimal sampling for Bayesian regression and rare event statistics using few samples46 cited
  • 2017Efficient Bayesian Experimentation Using an Expected Information Gain Lower Bound44 cited
  • 2017Sensor placement for calibration of spatially varying model parameters41 cited
  • 2016Sequential Bayesian optimal experimental design via approximate dynamic programming41 cited
  • 2015Fully Bayesian Experimental Design for Pharmacokinetic Studies40 cited
  • 2023A Fast and Scalable Computational Framework for Large-Scale High-Dimensional Bayesian Optimal Experimental Design33 cited
  • 2021Optimal design of experiments for optimization-based model calibration using Fisher information matrix32 cited
  • 2020Nesterov-aided stochastic gradient methods using Laplace approximation for Bayesian design optimization31 cited
  • 2021Surrogate-based sequential Bayesian experimental design using non-stationary Gaussian Processes29 cited
  • 2018Bayesian adaptation of chaos representations using variational inference and sampling on geodesics24 cited
  • 2019Simulation and Sensor Optimization for Multifidelity Dynamics Model Calibration11 cited
  • 2015Variational Bayesian strategies for high-dimensional, stochastic design problems9 cited