SIAM-ASA Journal on Uncertainty Quantification

Papers
(The median citation count of SIAM-ASA Journal on Uncertainty Quantification is 2. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-11-01 to 2024-11-01.)
ArticleCitations
Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark121
A Quasi-Monte Carlo Method for Optimal Control Under Uncertainty27
Cross-Entropy-Based Importance Sampling with Failure-Informed Dimension Reduction for Rare Event Simulation22
Stochastic Normalizing Flows for Inverse Problems: A Markov Chains Viewpoint20
Output-Weighted Optimal Sampling for Bayesian Experimental Design and Uncertainty Quantification18
Computing Shapley Effects for Sensitivity Analysis17
Fokker--Planck Particle Systems for Bayesian Inference: Computational Approaches17
Multilevel Monte Carlo Finite Difference Methods for Fractional Conservation Laws with Random Data14
Parameter Estimation in an SPDE Model for Cell Repolarization14
Unbiased Inference for Discretely Observed Hidden Markov Model Diffusions13
Optimal Design of Large-scale Bayesian Linear Inverse Problems Under Reducible Model Uncertainty: Good to Know What You Don't Know11
Taylor Approximation for Chance Constrained Optimization Problems Governed by Partial Differential Equations with High-Dimensional Random Parameters11
Global Sensitivity Analysis and Wasserstein Spaces11
A Spline Dimensional Decomposition for Uncertainty Quantification in High Dimensions10
GAN-Based Priors for Quantifying Uncertainty in Supervised Learning10
Uncertainty Quantification for the BGK Model of the Boltzmann Equation Using Multilevel Variance Reduced Monte Carlo Methods10
A Fast and Scalable Computational Framework for Large-Scale High-Dimensional Bayesian Optimal Experimental Design9
Nonlinear Reduced Models for State and Parameter Estimation9
Linked Gaussian Process Emulation for Systems of Computer Models Using Matérn Kernels and Adaptive Design9
Generalized Sparse Bayesian Learning and Application to Image Reconstruction9
Efficient Estimation of the ANOVA Mean Dimension, with an Application to Neural Net Classification9
Emulation of Stochastic Simulators Using Generalized Lambda Models9
PDE-Constrained Optimal Control Problems with Uncertain Parameters using SAGA9
Multifidelity Approximate Bayesian Computation with Sequential Monte Carlo Parameter Sampling9
Scaling Up Bayesian Uncertainty Quantification for Inverse Problems Using Deep Neural Networks8
Quantifying Truncation-Related Uncertainties in Unsteady Fluid Dynamics Reduced Order Models8
APIK: Active Physics-Informed Kriging Model with Partial Differential Equations8
Convergence Rates for Learning Linear Operators from Noisy Data8
On the Asymptotical Regularization for Linear Inverse Problems in Presence of White Noise8
A Convex Optimization Framework for the Inverse Problem of Identifying a Random Parameter in a Stochastic Partial Differential Equation8
Asymptotic Analysis of Multilevel Best Linear Unbiased Estimators8
Quasi-Monte Carlo Finite Element Analysis for Wave Propagation in Heterogeneous Random Media8
A Hybrid Gibbs Sampler for Edge-Preserving Tomographic Reconstruction with Uncertain View Angles7
Scaled Vecchia Approximation for Fast Computer-Model Emulation7
Empirical Bayesian Inference Using a Support Informed Prior7
EzGP: Easy-to-Interpret Gaussian Process Models for Computer Experiments with Both Quantitative and Qualitative Factors7
A Lagged Particle Filter for Stable Filtering of Certain High-Dimensional State-Space Models7
Stability of Gibbs Posteriors from the Wasserstein Loss for Bayesian Full Waveform Inversion7
Density Estimation by Randomized Quasi-Monte Carlo7
Joint Online Parameter Estimation and Optimal Sensor Placement for the Partially Observed Stochastic Advection-Diffusion Equation6
A Stochastic Levenberg--Marquardt Method Using Random Models with Complexity Results6
Multilevel Ensemble Kalman–Bucy Filters6
Representing Model Discrepancy in Bound-to-Bound Data Collaboration6
A Generalized Kernel Method for Global Sensitivity Analysis6
Uncertainty Quantification of Inclusion Boundaries in the Context of X-Ray Tomography6
Instances of Computational Optimal Recovery: Dealing with Observation Errors5
Deep Learning in High Dimension: Neural Network Expression Rates for Analytic Functions in \(\pmb{L^2(\mathbb{R}^d,\gamma_d)}\)5
Quantifying and Managing Uncertainty in Piecewise-Deterministic Markov Processes5
Ensemble Approximate Control Variate Estimators: Applications to MultiFidelity Importance Sampling5
Reproducing Kernel Hilbert Spaces, Polynomials, and the Classical Moment Problem5
Analysis of Nested Multilevel Monte Carlo Using Approximate Normal Random Variables5
Post hoc Uncertainty Quantification for Remote Sensing Observing Systems5
Model Error Estimation Using the Expectation Maximization Algorithm and a Particle Flow Filter5
Statistical Finite Elements via Langevin Dynamics5
Can We Trust Bayesian Uncertainty Quantification from Gaussian Process Priors with Squared Exponential Covariance Kernel?5
Optimization-Based Markov Chain Monte Carlo Methods for Nonlinear Hierarchical Statistical Inverse Problems5
Ensemble-Based Gradient Inference for Particle Methods in Optimization and Sampling4
Estimation of Ordinary Differential Equation Models with Discretization Error Quantification4
Bayesian Inference of an Uncertain Generalized Diffusion Operator4
Deep Neural Network Surrogates for Nonsmooth Quantities of Interest in Shape Uncertainty Quantification4
Large Deviation Theory-based Adaptive Importance Sampling for Rare Events in High Dimensions4
Generative Stochastic Modeling of Strongly Nonlinear Flows with Non-Gaussian Statistics4
Multilevel Markov Chain Monte Carlo for Bayesian Inversion of Parabolic Partial Differential Equations under Gaussian Prior4
Computer Model Calibration with Time Series Data Using Deep Learning and Quantile Regression4
Two-Level a Posteriori Error Estimation for Adaptive Multilevel Stochastic Galerkin Finite Element Method4
Gaussian Processes with Input Location Error and Applications to the Composite Parts Assembly Process4
Cross-Validation--based Adaptive Sampling for Gaussian Process Models4
Asymptotic Theory of \(\boldsymbol \ell _1\) -Regularized PDE Identification from a Single Noisy Trajectory4
Ensemble Markov Chain Monte Carlo with Teleporting Walkers4
A Variational Inference Approach to Inverse Problems with Gamma Hyperpriors4
Numerical Approximation of Optimal Convergence for Fractional Elliptic Equations with Additive Fractional Gaussian Noise4
Continuum Covariance Propagation for Understanding Variance Loss in Advective Systems4
Linear Parabolic Problems in Random Moving Domains3
On Unbiased Estimation for Discretized Models3
Sparse Online Variational Bayesian Regression3
An Inverse Random Source Problem for the Biharmonic Wave Equation3
Certified Dimension Reduction for Bayesian Updating with the Cross-Entropy Method3
On the Deep Active-Subspace Method3
Finite Element Representations of Gaussian Processes: Balancing Numerical and Statistical Accuracy3
Variance Reduction for Dependent Sequences with Applications to Stochastic Gradient MCMC3
Using Coupling Methods to Estimate Sample Quality of Stochastic Differential Equations3
A Nonparametric Bayesian Framework for Uncertainty Quantification in Stochastic Simulation3
A Trade-Off Between Explorations and Repetitions for Estimators of Two Global Sensitivity Indices in Stochastic Models Induced by Probability Measures3
Deep Surrogate Accelerated Delayed-Acceptance Hamiltonian Monte Carlo for Bayesian Inference of Spatio-Temporal Heat Fluxes in Rotating Disc Systems3
A Theoretical Framework of the Scaled Gaussian Stochastic Process in Prediction and Calibration3
Sampling-based Spotlight SAR Image Reconstruction from Phase History Data for Speckle Reduction and Uncertainty Quantification3
Evaluating Forecasts for High-Impact Events Using Transformed Kernel Scores3
Strong Rates of Convergence of a Splitting Scheme for Schrödinger Equations with Nonlocal Interaction Cubic Nonlinearity and White Noise Dispersion3
Quantifying Spatio-Temporal Boundary Condition Uncertainty for the North American Deglaciation3
Rank Bounds for Approximating Gaussian Densities in the Tensor-Train Format3
Analysis of a Class of Multilevel Markov Chain Monte Carlo Algorithms Based on Independent Metropolis–Hastings3
Lagrangian Uncertainty Quantification and Information Inequalities for Stochastic Flows2
Superfloe Parameterization with Physics Constraints for Uncertainty Quantification of Sea Ice Floes2
Parameter Selection in Gaussian Process Interpolation: An Empirical Study of Selection Criteria2
An Order-Theoretic Perspective on Modes and Maximum A Posteriori Estimation in Bayesian Inverse Problems2
Context-Aware Surrogate Modeling for Balancing Approximation and Sampling Costs in Multifidelity Importance Sampling and Bayesian Inverse Problems2
On the Generalized Langevin Equation for Simulated Annealing2
Multilevel Delayed Acceptance MCMC2
Risk-Adapted Optimal Experimental Design2
Finite Sample Approximations of Exact and Entropic Wasserstein Distances Between Covariance Operators and Gaussian Processes2
Lattice Boltzmann Method for Stochastic Convection-Diffusion Equations2
A Higher Order Unscented Transform2
Efficient Computation of Extreme Excursion Probabilities for Dynamical Systems through Rice's Formula2
Complete Deterministic Dynamics and Spectral Decomposition of the Linear Ensemble Kalman Inversion2
Goal-Oriented Shapley Effects with Special Attention to the Quantile-Oriented Case2
Calculation of Epidemic First Passage and Peak Time Probability Distributions2
On the Saturation Phenomenon of Stochastic Gradient Descent for Linear Inverse Problems2
Sequential Design of Computer Experiments for the Computation of Bayesian Model Evidence2
Wasserstein Sensitivity of Risk and Uncertainty Propagation2
Stacking Designs: Designing Multifidelity Computer Experiments with Target Predictive Accuracy2
Objective Frequentist Uncertainty Quantification for Atmospheric \(\mathrm{CO}_2\) Retrievals2
0.071971893310547