Pages that link to "Item:Q2767526"
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The following pages link to Bayesian calibration of computer models. (With discussion) (Q2767526):
Displaying 50 items.
- Adaptive multi-fidelity polynomial chaos approach to Bayesian inference in inverse problems (Q2214560) (← links)
- Structured Bayesian Gaussian process latent variable model: applications to data-driven dimensionality reduction and high-dimensional inversion (Q2214630) (← links)
- Bi-fidelity stochastic gradient descent for structural optimization under uncertainty (Q2221705) (← links)
- Error estimation in coupled multi-physics models (Q2222328) (← links)
- Demonstration of the relationship between sensitivity and identifiability for inverse uncertainty quantification (Q2222401) (← links)
- An adaptive reduced basis ANOVA method for high-dimensional Bayesian inverse problems (Q2222423) (← links)
- Flexible iterative ensemble smoother for calibration of perfect and imperfect models (Q2225354) (← links)
- Dynamic simulation metamodeling using Mars: a case of radar simulation (Q2228788) (← links)
- A deep learning driven pseudospectral PCE based FFT homogenization algorithm for complex microstructures (Q2237801) (← links)
- Robust optimisation of computationally expensive models using adaptive multi-fidelity emulation (Q2240278) (← links)
- Novel method for a posteriori uncertainty quantification in wildland fire spread simulation (Q2241771) (← links)
- Bayes linear analysis for ordinary differential equations (Q2242017) (← links)
- Calibration of a radiation quality model for sparse and uncertain data (Q2242528) (← links)
- Rapid design of metamaterials via multitarget Bayesian optimization (Q2245155) (← links)
- Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian processes (Q2246340) (← links)
- Residual Gaussian process: a tractable nonparametric Bayesian emulator for multi-fidelity simulations (Q2247250) (← links)
- A Bayesian approach to crop model calibration under unknown error covariance (Q2259939) (← links)
- Assessing first-order emulator inference for physical parameters in nonlinear mechanistic models (Q2261036) (← links)
- Modeling space-time dynamics of aerosols using satellite data and atmospheric transport model output (Q2261039) (← links)
- Verifying reification with application to a rainfall-runoff computer simulator (Q2261041) (← links)
- Calibration of numerical model output using nonparametric spatial density functions (Q2261043) (← links)
- Quantifying simulator discrepancy in discrete-time dynamical simulators (Q2261045) (← links)
- Comparing and blending regional climate model predictions for the American Southwest (Q2261049) (← links)
- Computer model calibration based on image warping metrics: an application for sea ice deformation (Q2272999) (← links)
- Estimating the rate constant from biosensor data via an adaptive variational Bayesian approach (Q2291491) (← links)
- Bayesian uncertainty analysis for complex physical systems modelled by computer simulators with applications to tipping points (Q2297476) (← links)
- Stratified random sampling for dependent inputs in Monte Carlo simulations from computer experiments (Q2301061) (← links)
- Iterative construction of Gaussian process surrogate models for Bayesian inference (Q2301102) (← links)
- Probabilistic solutions to ordinary differential equations as nonlinear Bayesian filtering: a new perspective (Q2302458) (← links)
- Calibration experimental design considering field response and model uncertainty (Q2309083) (← links)
- Bayesian model selection using automatic relevance determination for nonlinear dynamical systems (Q2309843) (← links)
- An estimation algorithm for fast Kriging surrogates of computer models with unstructured multiple outputs (Q2309874) (← links)
- A computational framework for Bayesian inference in plasticity models characterisation (Q2309896) (← links)
- Jointly robust prior for Gaussian stochastic process in emulation, calibration and variable selection (Q2316987) (← links)
- Diagnosing forward operator error using optimal transport (Q2330670) (← links)
- Physics-informed covariance kernel for model-form uncertainty quantification with application to turbulent flows (Q2331882) (← links)
- System design of stochastic models using robustness of temporal properties (Q2348023) (← links)
- Full scale multi-output Gaussian process emulator with nonseparable auto-covariance functions (Q2374734) (← links)
- A paradigm for data-driven predictive modeling using field inversion and machine learning (Q2374961) (← links)
- Emulation of dynamic simulators with application to hydrology (Q2375076) (← links)
- Numerical strategy for model correction using physical constraints (Q2375092) (← links)
- Bayesian inference of nonlinear unsteady aerodynamics from aeroelastic limit cycle oscillations (Q2375247) (← links)
- Default priors for Gaussioan processes (Q2388348) (← links)
- Multilevel model reduction for uncertainty quantification in computational structural dynamics (Q2400060) (← links)
- On the validity and errors of the pseudo-first-order kinetics in ligand-receptor binding (Q2407278) (← links)
- Bayesian calibration, validation and uncertainty quantification for predictive modelling of tumour growth: a tutorial (Q2408846) (← links)
- Extreme value analysis for evaluating ozone control strategies (Q2443142) (← links)
- Virtual model validation of complex multiscale systems: applications to nonlinear elastostatics (Q2450416) (← links)
- Uncertainty updating in the description of coupled heat and moisture transport in heterogeneous materials (Q2451309) (← links)
- Computer model validation with functional output (Q2466674) (← links)
