Pages that link to "Item:Q2872960"

The following pages link to Uncertainty quantification. Theory, implementation, and applications (Q2872960):

Displaying 50 items.

• Stable splittings of Hilbert spaces of functions of infinitely many variables (Q2360671) (← links)
• A Hankel norm for quadrature rules solving random linear dynamical systems (Q2406650) (← links)
• Uncertainty theory with applications (Q2418592) (← links)
• \(\mathrm{L}^p\)-calculus approach to the random autonomous linear differential equation with discrete delay (Q2424132) (← links)
• Verification of internal risk measure estimates (Q2520725) (← links)
• Uncertainty quantification for hybrid random logistic models with harvesting via density functions (Q2675546) (← links)
• Designing experimental conditions to use the Lotka-Volterra model to infer tumor cell line interaction types (Q2678765) (← links)
• Uncertainty quantification in scientific machine learning: methods, metrics, and comparisons (Q2681129) (← links)
• Probabilistic analysis of a general class of nonlinear random differential equations with state-dependent impulsive terms via probability density functions (Q2685780) (← links)
• A spectral surrogate model for stochastic simulators computed from trajectory samples (Q2686878) (← links)
• An axiomatic calculus of uncertainty (Q2751824) (← links)
• Nonparametric Uncertainty Quantification for Stochastic Gradient Flows (Q2945163) (← links)
• Uncertainty Quantification in Graph-Based Classification of High Dimensional Data (Q3176234) (← links)
• An Applied/Computational Mathematician’s View of Uncertainty Quantification for Complex Systems (Q3296312) (← links)
• Basic Aspects of Uncertainty II. The Inverse Estimations (Q4466881) (← links)
• Parameter identification and sensitivity analysis for a phytoplankton competition model (Q4554150) (← links)
• A Primer on Noise-Induced Transitions in Applied Dynamical Systems (Q4554910) (← links)
• Bayesian model calibration and uncertainty quantification for an HIV model using adaptive Metropolis algorithms (Q4563450) (← links)
• TAMING UNCERTAINTY: THE LIMITS TO QUANTIFICATION (Q4563758) (← links)
• A Probabilistic Subspace Bound with Application to Active Subspaces (Q4584918) (← links)
• Nonintrusive Uncertainty Analysis of Fluid-Structure Interaction with Spatially Adaptive Sparse Grids and Polynomial Chaos Expansion (Q4610141) (← links)
• Uncertainty Quantification for Low-Frequency, Time-Harmonic Maxwell Equations with Stochastic Conductivity Models (Q4611518) (← links)
• (Q4636971) (← links)
• Uncertainty Quantification and Predictive Computational Science (Q4647294) (← links)
• Uncertainty Quantification in Case of Imperfect Models: A Non‐Bayesian Approach (Q4685451) (← links)
• Multilevel Monte Carlo Covariance Estimation for the Computation of Sobol' Indices (Q4960977) (← links)
• (Q4983392) (← links)
• Beyond the hypothesis of boundedness for the random coefficient of Airy, Hermite and Laguerre differential equations with uncertainties (Q4986445) (← links)
• Lattice Boltzmann Method for Stochastic Convection-Diffusion Equations (Q4995115) (← links)
• On forward and inverse uncertainty quantification for models involving hysteresis operators (Q5001320) (← links)
• A Tutorial on Sobol’ Global Sensitivity Analysis Applied to Biological Models (Q5013984) (← links)
• How to Gauge a Combination of Uncertainties of Different Type: General Foundations (Q5015927) (← links)
• Bayesian estimation and uncertainty quantification in models of urea hydrolysis by<i>E. coli</i>biofilms (Q5036770) (← links)
• (Q5053246) (← links)
• On the multi-species Boltzmann equation with uncertainty and its stochastic Galerkin approximation (Q5074373) (← links)
• On Uncertainty Quantification for Models Involving Hysteresis Operators (Q5115142) (← links)
• Uncertainty Quantification for Stochastic Approximation Limits Using Chaos Expansion (Q5119639) (← links)
• Parameter Identification in Uncertain Scalar Conservation Laws Discretized with the Discontinuous Stochastic Galerkin Scheme (Q5162353) (← links)
• Analysis and Application of Single Level, Multi-Level Monte Carlo and Quasi-Monte Carlo Finite Element Methods for Time-Dependent Maxwell's Equations with Random Inputs (Q5163181) (← links)
• Solving Random Ordinary and Partial Differential Equations Through the Probability Density Function: Theory and Computing with Applications (Q5223401) (← links)
• (Q5225111) (← links)
• Gradient-Free Construction of Active Subspaces for Dimension Reduction in Complex Models with Applications to Neutronics (Q5228351) (← links)
• On Nonintrusive Uncertainty Quantification and Surrogate Model Construction in Particle Accelerator Modeling (Q5228361) (← links)
• SDE Based Regression for Linear Random PDEs (Q5275045) (← links)
• A Geometric Approach to Dynamical Model Order Reduction (Q5373924) (← links)
• Uncertainty Quantification by Alternative Decompositions of Multivariate Functions (Q5404624) (← links)
• Uncertainty quantification in the numerical solution of coupled systems by involutive completion (Q5501886) (← links)
• Solving Random Ordinary Differential Equations on GPU Clusters using Multiple Levels of Parallelism (Q5739951) (← links)
• Parameter Selection and Verification Techniques Based on Global Sensitivity Analysis Illustrated for an HIV Model (Q5741179) (← links)
• A local sensitivity analysis in Landau damping for the kinetic Kuramoto equation with random inputs (Q5858932) (← links)