Pages that link to "Item:Q2936501"

The following pages link to Learning about physical parameters: the importance of model discrepancy (Q2936501):

Displaying 50 items.

• Use of difference-based methods to explore statistical and mathematical model discrepancy in inverse problems (Q318177) (← links)
• Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier-Stokes simulations: a data-driven, physics-informed Bayesian approach (Q525932) (← links)
• Bayesian model selection framework for identifying growth patterns in filamentous fungi (Q738557) (← links)
• Understanding hormonal crosstalk in \textit{Arabidopsis} root development via emulation and history matching (Q830633) (← links)
• Advances in modeling model discrepancy: comment on Wu and Browne (Q888045) (← links)
• Bayesian pollution source identification via an inverse physics model (Q1727923) (← links)
• Dynamic Bayesian influenza forecasting in the United States with hierarchical discrepancy (with discussion) (Q1738132) (← links)
• A hierarchical spatiotemporal statistical model motivated by glaciology (Q2009141) (← 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 fast and calibrated computer model emulator: an empirical Bayes approach (Q2058785) (← links)
• Polynomial surrogates for Bayesian traveltime tomography (Q2062365) (← links)
• Analyzing stochastic computer models: a review with opportunities (Q2075795) (← links)
• Structured discrepancy in Bayesian model calibration for ChemCam on the Mars Curiosity rover (Q2078788) (← links)
• Data-driven uncertainty quantification in macroscopic traffic flow models (Q2095539) (← links)
• Identification of model uncertainty via optimal design of experiments applied to a mechanical press (Q2138321) (← links)
• Inference for stochastic kinetic models from multiple data sources for joint estimation of infection dynamics from aggregate reports and virological data (Q2154191) (← links)
• A higher-order singular value decomposition tensor emulator for spatiotemporal simulators (Q2163486) (← links)
• Seismic data assimilation with an imperfect model (Q2186006) (← 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)
• Demonstration of the relationship between sensitivity and identifiability for inverse uncertainty quantification (Q2222401) (← links)
• Flexible iterative ensemble smoother for calibration of perfect and imperfect models (Q2225354) (← links)
• Accelerating uncertainty quantification of groundwater flow modelling using a deep neural network proxy (Q2237307) (← links)
• Bayes linear analysis for ordinary differential equations (Q2242017) (← links)
• Tracking for parameter and state estimation in possibly misspecified partially observed linear ordinary differential equations (Q2317251) (← links)
• Physics-informed covariance kernel for model-form uncertainty quantification with application to turbulent flows (Q2331882) (← links)
• A paradigm for data-driven predictive modeling using field inversion and machine learning (Q2374961) (← links)
• Numerical strategy for model correction using physical constraints (Q2375092) (← links)
• Data-driven learning of differential equations: combining data and model uncertainty (Q2686515) (← links)
• Optimal Control and Additive Perturbations Help in Estimating Ill-Posed and Uncertain Dynamical Systems (Q4559701) (← links)
• Identification of dynamical systems with structured uncertainty (Q4563454) (← links)
• Iterative updating of model error for Bayesian inversion (Q4607829) (← links)
• Calibrating a Stochastic, Agent-Based Model Using Quantile-Based Emulation (Q4611533) (← links)
• Adaptive Numerical Designs for the Calibration of Computer Codes (Q4636370) (← links)
• Efficient History Matching of a High Dimensional Individual-Based HIV Transmission Model (Q4636404) (← links)
• Predicting the Output From a Stochastic Computer Model When a Deterministic Approximation is Available (Q5066748) (← links)
• Bayesian model calibration for vacuum-ultraviolet photoionisation mass spectrometry (Q5092618) (← links)
• Bayesian Optimal Design for Ordinary Differential Equation Models With Application in Biological Science (Q5130598) (← links)
• Dealing with Measurement Uncertainties as Nuisance Parameters in Bayesian Model Calibration (Q5139352) (← links)
• Considering discrepancy when calibrating a mechanistic electrophysiology model (Q5154219) (← links)
• Uncertainty Quantification for Computer Models With Spatial Output Using Calibration-Optimal Bases (Q5208085) (← links)
• Prediction Uncertainties beyond the Range of Experience: A Case Study in Inertial Confinement Fusion Implosion Experiments (Q5237170) (← links)
• Representing Model Discrepancy in Bound-to-Bound Data Collaboration (Q5858423) (← links)
• Estimation of Ordinary Differential Equation Models with Discretization Error Quantification (Q5858427) (← links)
• Computer Model Calibration with Time Series Data Using Deep Learning and Quantile Regression (Q5862894) (← links)
• Bayesian Projected Calibration of Computer Models (Q5881976) (← links)
• On global normal linear approximations for nonlinear Bayesian inverse problems (Q5886385) (← links)
• A surrogate-assisted uncertainty-aware Bayesian validation framework and its application to coupling free flow and porous-medium flow (Q6050704) (← links)
• Hyper-differential sensitivity analysis with respect to model discrepancy: optimal solution updating (Q6097647) (← links)