Pages that link to "Item:Q2767526"

The following pages link to Bayesian calibration of computer models. (With discussion) (Q2767526):

Displaying 50 items.

• Calibration of imperfect models to biased observations (Q1710300) (← links)
• Bayes linear analysis of risks in sequential optimal design problems (Q1711561) (← links)
• Multimodal, high-dimensional, model-based, Bayesian inverse problems with applications in biomechanics (Q1714421) (← links)
• Bayesian prediction for physical models with application to the optimization of the synthesis of pharmaceutical products using chemical kinetics (Q1727860) (← links)
• Bayesian pollution source identification via an inverse physics model (Q1727923) (← links)
• Emulator-assisted reduced-rank ecological data assimilation for nonlinear multivariate dynamical spatio-temporal processes (Q1731188) (← links)
• Bayesian sequential data collection for stochastic simulation calibration (Q1735194) (← links)
• Dynamic Bayesian influenza forecasting in the United States with hierarchical discrepancy (with discussion) (Q1738132) (← links)
• Uncertainty aggregation and reduction in structure-material performance prediction (Q1753925) (← links)
• Statistics in atmospheric science (Q1764311) (← links)
• Assessment of uncertainties in hot-wire anemometry and oil-film interferometry measurements for wall-bounded turbulent flows (Q1784584) (← links)
• Penalising model component complexity: a principled, practical approach to constructing priors (Q1790379) (← links)
• Calibration and Bayesian learning. (Q1867026) (← links)
• Workshop on statistical approaches for the evaluation of complex computer models (Q1872604) (← links)
• Modelling, making inferences and making decisions: The roles of sensitivity analysis (Q1876462) (← links)
• Indistinguishable states. II: The imperfect model scenario (Q1881719) (← links)
• A mechanistic dynamic emulator (Q1926243) (← links)
• Calibration of computer models with multivariate output (Q1927177) (← links)
• The effect of the nugget on Gaussian process emulators of computer models (Q1927203) (← links)
• Inference for population dynamics in the Neolithic period (Q1939990) (← links)
• Inverse dispersion for an unknown number of sources: model selection and uncertainty analysis (Q1954386) (← links)
• Uncertainty quantification with risk measures in production planning (Q1980955) (← links)
• Uncertainty quantification in multiscale simulation of woven fiber composites (Q1986218) (← links)
• Epistemic uncertainty-based model validation via interval propagation and parameter calibration (Q1986379) (← links)
• Bayesian assessment of uncertainty in viscosity closure models for turbidity currents computations (Q1986420) (← links)
• Machine-learning error models for approximate solutions to parameterized systems of nonlinear equations (Q1987897) (← links)
• A data-driven framework for sparsity-enhanced surrogates with arbitrary mutually dependent randomness (Q1987969) (← links)
• Bayesian modeling of inconsistent plastic response due to material variability (Q1988100) (← links)
• Robust Gaussian stochastic process emulation (Q1991689) (← links)
• Emulating dynamic non-linear simulators using Gaussian processes (Q2002727) (← links)
• Modelling of a thermomechanically coupled forming process based on functional outputs from a finite element analysis and from experimental measurements (Q2006885) (← links)
• A hierarchical spatiotemporal statistical model motivated by glaciology (Q2009141) (← links)
• Quantification of predictive uncertainty in models of FtsZ ring assembly in \textit{Escherichia coli} (Q2010867) (← links)
• A dynamic bi-orthogonal field equation approach to efficient Bayesian inversion (Q2011888) (← links)
• Fundamental issues in the representation and propagation of uncertain equation of state information in shock hydrodynamics (Q2014900) (← links)
• Mean-field and full-field homogenization with polymorphic uncertain geometry and material parameters (Q2020721) (← links)
• Modeling strength and failure variability due to porosity in additively manufactured metals (Q2020756) (← links)
• A sequential calibration and validation framework for model uncertainty quantification and reduction (Q2021198) (← links)
• Data fusion for uncertainty quantification with non-intrusive polynomial chaos (Q2021255) (← links)
• Bayesian calibration of computer models based on Takagi-Sugeno fuzzy models (Q2021858) (← links)
• The statistical finite element method (statFEM) for coherent synthesis of observation data and model predictions (Q2022037) (← links)
• A neural network-based framework for financial model calibration (Q2022121) (← links)
• Randomized reduced forward models for efficient Metropolis-Hastings MCMC, with application to subsurface fluid flow and capacitance tomography (Q2023287) (← links)
• Computed tomography reconstruction with uncertain view angles by iteratively updated model discrepancy (Q2033298) (← links)
• Estimation of an improved surrogate model in uncertainty quantification by neural networks (Q2042433) (← links)
• Estimation of a density using an improved surrogate model (Q2044316) (← links)
• Calibrating expert assessments using hierarchical Gaussian process models (Q2057359) (← links)
• Parallel Gaussian process surrogate Bayesian inference with noisy likelihood evaluations (Q2057377) (← links)
• Sequential Bayesian optimal experimental design for structural reliability analysis (Q2058731) (← links)
• A fast and calibrated computer model emulator: an empirical Bayes approach (Q2058785) (← links)