Pages that link to "Item:Q2767526"

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

Displaying 50 items.

• Bayesian numerical methods for nonlinear partial differential equations (Q2058795) (← links)
• Learning quantities of interest from dynamical systems for observation-consistent inversion (Q2060144) (← links)
• Polynomial surrogates for Bayesian traveltime tomography (Q2062365) (← links)
• Emulation-accelerated Hamiltonian Monte Carlo algorithms for parameter estimation and uncertainty quantification in differential equation models (Q2066738) (← links)
• Bayesian optimization of functional output in inverse problems (Q2069152) (← links)
• Analyzing stochastic computer models: a review with opportunities (Q2075795) (← links)
• At the crossroads of simulation and data analytics (Q2076004) (← links)
• Assessing the reliability of wind power operations under a changing climate with a non-Gaussian bias correction (Q2078298) (← links)
• Effective model calibration via sensible variable identification and adjustment with application to composite fuselage simulation (Q2078752) (← links)
• Structured discrepancy in Bayesian model calibration for ChemCam on the Mars Curiosity rover (Q2078788) (← links)
• Estimating functional parameters for understanding the impact of weather and government interventions on COVID-19 outbreak (Q2080764) (← links)
• A spatial causal analysis of wildland fire-contributed \(\mathrm{PM}_{2.5}\) using numerical model output (Q2080787) (← links)
• Non-intrusive estimation of model error and discrepancy in dynamics models (Q2088335) (← links)
• The SPDE approach to Matérn fields: graph representations (Q2092895) (← links)
• Data-driven uncertainty quantification in macroscopic traffic flow models (Q2095539) (← links)
• Emulation of cardiac mechanics using graph neural networks (Q2096869) (← links)
• \texttt{CAMERA}: a method for cost-aware, adaptive, multifidelity, efficient reliability analysis (Q2099759) (← links)
• Variational inference with vine copulas: an efficient approach for Bayesian computer model calibration (Q2110192) (← links)
• Bayesian fixed-domain asymptotics for covariance parameters in a Gaussian process model (Q2112815) (← links)
• Hierarchical sparse Cholesky decomposition with applications to high-dimensional spatio-temporal filtering (Q2114043) (← links)
• Surrogate modeling of hydrodynamic forces between multiple floating bodies through a hierarchical interaction decomposition (Q2123359) (← links)
• Calibrate, emulate, sample (Q2123875) (← links)
• Fixed inducing points online Bayesian calibration for computer models with an application to a scale-resolving CFD simulation (Q2124026) (← links)
• On generalized residual network for deep learning of unknown dynamical systems (Q2124404) (← links)
• Nonlinear sparse Bayesian learning for physics-based models (Q2126972) (← links)
• Robust calibration of numerical models based on relative regret (Q2127020) (← links)
• Deep coregionalization for the emulation of simulation-based spatial-temporal fields (Q2128339) (← links)
• Calibration and prediction for the inexact SIR model (Q2130340) (← links)
• Bayesian model inversion using stochastic spectral embedding (Q2131057) (← links)
• Model error propagation from experimental to prediction configuration (Q2132609) (← links)
• Identification of model uncertainty via optimal design of experiments applied to a mechanical press (Q2138321) (← links)
• Probabilistic learning inference of boundary value problem with uncertainties based on Kullback-Leibler divergence under implicit constraints (Q2142219) (← links)
• A predictive multiphase model of silica aerogels for building envelope insulations (Q2150246) (← links)
• Adaptive design for Gaussian process regression under censoring (Q2154177) (← links)
• Batch-sequential design and heteroskedastic surrogate modeling for delta smelt conservation (Q2154181) (← links)
• Data-driven uncertainty quantification in computational human head models (Q2160383) (← links)
• Variational inference with NoFAS: normalizing flow with adaptive surrogate for computationally expensive models (Q2162034) (← links)
• A higher-order singular value decomposition tensor emulator for spatiotemporal simulators (Q2163486) (← links)
• Parameter calibration in wake effect simulation model with stochastic gradient descent and stratified sampling (Q2170435) (← links)
• Ice model calibration using semicontinuous spatial data (Q2170447) (← links)
• Variational system identification of the partial differential equations governing the physics of pattern-formation: inference under varying fidelity and noise (Q2173625) (← links)
• Evaluation of ensemble methods for quantifying uncertainties in steady-state CFD applications with small ensemble sizes (Q2180033) (← links)
• Time-series machine-learning error models for approximate solutions to parameterized dynamical systems (Q2184303) (← links)
• Adaptive method for indirect identification of the statistical properties of random fields in a Bayesian framework (Q2184398) (← links)
• A bi-fidelity surrogate modeling approach for uncertainty propagation in three-dimensional hemodynamic simulations (Q2184449) (← links)
• Enforcing boundary conditions on physical fields in Bayesian inversion (Q2186856) (← links)
• A regularization method for the parameter estimation problem in ordinary differential equations via discrete optimal control theory (Q2189116) (← links)
• A fast particle-based approach for calibrating a 3-D model of the Antarctic ice sheet (Q2194450) (← links)
• Coherent combination of probabilistic outputs for group decision making: an algebraic approach (Q2197159) (← links)
• Sampling of Bayesian posteriors with a non-Gaussian probabilistic learning on manifolds from a small dataset (Q2209715) (← links)