OOIR: Observatory of International Research

Papers

(The median citation count of International Journal for Uncertainty Quantification is 0. 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 2021-08-01 to 2025-08-01.)

Article	Citations
COMPUTATIONAL CHALLENGES IN SAMPLING AND REPRESENTATION OF UNCERTAIN REACTION KINETICS IN LARGE DIMENSIONS	31
Bayesian³ Active learning for regularized arbitrary multi-element polynomial chaos using information theory	29
SENSITIVITY ANALYSIS WITH CORRELATED INPUTS: COMPARISON OF INDICES FOR THE LINEAR CASE	24
	13
CONTROL VARIATE POLYNOMIAL CHAOS: OPTIMAL FUSION OF SAMPLING AND SURROGATES FOR MULTIFIDELITY UNCERTAINTY QUANTIFICATION	11
A novel probabilistic transfer learning strategy for polynomial regression	10
	7
Uncertainty quantification for deep learning-based schemes for solving high-dimensional backward stochastic differential equations	7
COVARIANCE ESTIMATION USING h-STATISTICS IN MONTE CARLO AND MULTILEVEL MONTE CARLO METHODS	7
	7
MAJORIZATION AS A THEORY FOR UNCERTAINTY	7
SENSITIVITY ANALYSES OF A MULTIPHYSICS LONG-TERM CLOGGING MODEL FOR STEAM GENERATORS	6
Lp CONVERGENCE OF APPROXIMATE MAPS AND PROBABILITY DENSITIES FOR FORWARD AND INVERSE PROBLEMS IN UNCERTAINTY QUANTIFICATION	5
	5
IMPROVING ACCURACY AND COMPUTATIONAL EFFICIENCY OF OPTIMAL DESIGN OF EXPERIMENTS VIA GREEDY BACKWARD APPROACH	4
A FULLY BAYESIAN GRADIENT-FREE SUPERVISED DIMENSION REDUCTION METHOD USING GAUSSIAN PROCESSES	4
STRUCTURE-PRESERVING MODEL ORDER REDUCTION OF RANDOM PARAMETRIC LINEAR SYSTEMS VIA REGRESSION	4
INDEX	4
MEASURING INPUTS-OUTPUTS ASSOCIATION FOR TIME-DEPENDENT HAZARD MODELS UNDER SAFETY OBJECTIVES USING KERNELS	4
	4
PARALLEL PARTIAL EMULATION IN APPLICATIONS	4
Clustering based multiple anchors high-dimensional model representation	4
BAYESIAN PARAMETER INFERENCE FOR PARTIALLY OBSERVED DIFFUSIONS USING MULTILEVEL STOCHASTIC RUNGE-KUTTA METHODS	3
GLOBAL SENSITIVITY ANALYSIS USING DERIVATIVE-BASED SPARSE POINCARÉ CHAOS EXPANSIONS	3
	3

	3
LONG SHORT-TERM RELEVANCE LEARNING	3
	2
	2
UNCERTAINTY QUANTIFICATION AND GLOBAL SENSITIVITY ANALYSIS OF SEISMIC FRAGILITY CURVES USING KRIGING	2
PREFACE: RECENT ADVANCES IN GLOBAL SENSITIVITY ANALYSIS	2
MAXIMUM ENTROPY UNCERTAINTY MODELING AT THE FINITE ELEMENT LEVEL FOR HEATED STRUCTURES	2
A DOMAIN-DECOMPOSED VAE METHOD FOR BAYESIAN INVERSE PROBLEMS	2
STOCHASTIC GALERKIN METHOD AND PORT-HAMILTONIAN FORM FOR LINEAR FIRST-ORDER ORDINARY DIFFERENTIAL EQUATIONS	2
EFFICIENT CALIBRATION FOR HIGH-DIMENSIONAL COMPUTER MODEL OUTPUT USING BASIS METHODS	2
UNBIASED ESTIMATION OF THE VANILLA AND DETERMINISTIC ENSEMBLE KALMAN-BUCY FILTERS	2
A COMPREHENSIVE COMPARISON OF TOTAL-ORDER ESTIMATORS FOR GLOBAL SENSITIVITY ANALYSIS	2
AN ADAPTIVE STRATEGY FOR SEQUENTIAL DESIGNS OF MULTILEVEL COMPUTER EXPERIMENTS	2
SHAPLEY EFFECT ESTIMATION IN RELIABILITY-ORIENTED SENSITIVITY ANALYSIS WITH CORRELATED INPUTS BY IMPORTANCE SAMPLING	2
CLOSURE LAW MODEL UNCERTAINTY QUANTIFICATION	2
METHOD FOR THE ANALYSIS OF EPISTEMIC AND ALEATORY UNCERTAINTIES FOR A RELIABLE EVALUATION OF FAILURE OF ENGINEERING STRUCTURES	2
	1
	1
EFFICIENT APPROXIMATION OF HIGH-DIMENSIONAL EXPONENTIALS BY TENSOR NETWORKS	1
	1
	1
DISCREPANCY MODELING FOR MODEL CALIBRATION WITH MULTIVARIATE OUTPUT	1
A generalized likelihood-weighted optimal sampling algorithm for rare-event probability quantification	1
LIKELIHOOD AND DEPTH-BASED CRITERIA FOR COMPARING SIMULATION RESULTS WITH EXPERIMENTAL DATA, IN SUPPORT OF VALIDATION OF NUMERICAL SIMULATORS	1
MODEL ERROR ESTIMATION USING PEARSON SYSTEM WITH APPLICATION TO NONLINEAR WAVES IN COMPRESSIBLE FLOWS	1
QUANTIFICATION AND PROPAGATION OF MODEL-FORM UNCERTAINTIES IN RANS TURBULENCE MODELING VIA INTRUSIVE POLYNOMIAL CHAOS	1
MEAN-FIELD CONTROL VARIATE METHODS FOR KINETIC EQUATIONS WITH UNCERTAINTIES AND APPLICATIONS TO SOCIOECONOMIC SCIENCES	1
AUTOMATIC SELECTION OF BASIS-ADAPTIVE SPARSE POLYNOMIAL CHAOS EXPANSIONS FOR ENGINEERING APPLICATIONS	1
AN ENHANCED FRAMEWORK FOR MORRIS BY COMBINING WITH A SEQUENTIAL SAMPLING STRATEGY	1
MANIFOLD LEARNING-BASED POLYNOMIAL CHAOS EXPANSIONS FOR HIGH-DIMENSIONAL SURROGATE MODELS	1
COMBINED DATA AND DEEP LEARNING MODEL UNCERTAINTIES: AN APPLICATION TO THE MEASUREMENT OF SOLID FUEL REGRESSION RATE	1
EXTREME LEARNING MACHINES FOR VARIANCE-BASED GLOBAL SENSITIVITY ANALYSIS	1
A filtered multilevel Monte Carlo method for estimating the expectation of cell-centered discretized random fields	1
Efficient treatment of the model error in the calibration of computer codes: the Complete Maximum a Posteriori method	1
CALCULATING PROBABILITY DENSITIES WITH HOMOTOPY AND APPLICATIONS TO PARTICLE FILTERS	0
Learning a class of stochastic differential equations via numerics-informed Bayesian denoising	0
FIELD SENSITIVITY ANALYSIS OF TURBULENCE MODEL PARAMETERS FOR FLOW OVER A WING	0
STATISTICAL CLOSURE MODELING FOR REDUCED-ORDER MODELS OF STATIONARY SYSTEMS BY THE ROMES METHOD	0
HYPERDIFFERENTIAL SENSITIVITY ANALYSIS IN THE CONTEXT OF BAYESIAN INFERENCE APPLIED TO ICE-SHEET PROBLEMS	0
	0
LEARNING HIGH-DIMENSIONAL PROBABILITY DISTRIBUTIONS USING TREE TENSOR NETWORKS	0
A STOCHASTIC DOMAIN DECOMPOSITION AND POST-PROCESSING ALGORITHM FOR EPISTEMIC UNCERTAINTY QUANTIFICATION	0
A FETI-DP-BASED PARALLEL ALGORITHM FOR SOLVING HIGH DIMENSIONAL STOCHASTIC PDES USING COLLOCATION	0
SENSITIVITY ANALYSIS OF THE INFORMATION GAIN IN INFINITE-DIMENSIONAL BAYESIAN LINEAR INVERSE PROBLEMS	0
UNCERTAINTY ANALYSIS FOR EVOLUTION EQUATIONS	0
MULTILEVEL QUASI-MONTE CARLO FOR INTERVAL ANALYSIS	0
SPARSE TENSOR PRODUCT APPROXIMATION FOR A CLASS OF GENERALIZED METHOD OF MOMENTS ESTIMATORS	0
Stochastic Galerkin method for linear fractional differential equations	0
A BAYESIAN NEURAL NETWORK APPROACH TO MULTI-FIDELITY SURROGATE MODELING	0
DYNAMICAL LOW-RANK APPROXIMATION FOR BURGERS' EQUATION WITH UNCERTAINTY	0

	0
	0
UNCERTAINTY QUANTIFICATION BY GAUSSIAN RANDOM FIELDS FOR POINT-LIKE EMISSIONS FROM SATELLITE OBSERVATIONS	0
AdaAnn: ADAPTIVE ANNEALING SCHEDULER FOR PROBABILITY DENSITY APPROXIMATION	0
STOCHASTIC POLYNOMIAL CHAOS EXPANSIONS TO EMULATE STOCHASTIC SIMULATORS	0
FEEDBACK CONTROL FOR RANDOM, LINEAR HYPERBOLIC BALANCE LAWS	0
MIXED COVARIANCE FUNCTION KRIGING MODEL FOR UNCERTAINTY QUANTIFICATION	0
BAYESIAN IDENTIFICATION OF PYROLYSIS MODEL PARAMETERS FOR THERMAL PROTECTION MATERIALS USING AN ADAPTIVE GRADIENT-INFORMED SAMPLING ALGORITHM WITH APPLICATION TO A MARS ATMOSPHERIC ENTRY	0
CONTROL VARIATES WITH A DIMENSION REDUCED BAYESIAN MONTE CARLO SAMPLER	0
STOCHASTIC GALERKIN FINITE ELEMENT METHOD FOR NONLINEAR ELASTICITY AND APPLICATION TO REINFORCED CONCRETE MEMBERS	0
INDEX, VOLUME 12, 2022	0
	0
Stein Variational Rare Event Simulation	0
A DIMENSION-ADAPTIVE COMBINATION TECHNIQUE FOR UNCERTAINTY QUANTIFICATION	0
Stability and Convergence of Solutions to Stochastic Inverse Problems Using Approximate Probability Densities	0
STABLE LIKELIHOOD COMPUTATION FOR MACHINE LEARNING OF LINEAR DIFFERENTIAL OPERATORS WITH GAUSSIAN PROCESSES	0
ADAPTIVE STRATIFIED SAMPLING FOR NONSMOOTH PROBLEMS	0
APPLICATION OF GLOBAL SENSITIVITY ANALYSIS FOR IDENTIFICATION OF PROBABILISTIC DESIGN SPACES	0
HYPER-DIFFERENTIAL SENSITIVITY ANALYSIS FOR NONLINEAR BAYESIAN INVERSE PROBLEMS	0
BAYESIAN CALIBRATION WITH ADAPTIVE MODEL DISCREPANCY	0
EXTREMES OF VECTOR-VALUED PROCESSES BY FINITE DIMENSIONAL MODELS	0
	0
INDEX, VOLUME 13, 2023	0
VARIANCE-BASED SENSITIVITY OF BAYESIAN INVERSE PROBLEMS TO THE PRIOR DISTRIBUTION	0
PROBABILISTIC UNCERTAINTY PROPAGATION USING GAUSSIAN PROCESS SURROGATES	0
UNCERTAINTY QUANTIFICATION OF WATERFLOODING IN OIL RESERVOIRS COMPUTATIONAL SIMULATIONS USING A PROBABILISTIC LEARNING APPROACH	0
MULTILEVEL MONTE CARLO ESTIMATORS FOR DERIVATIVE-FREE OPTIMIZATION UNDER UNCERTAINTY	0
DECISION THEORETIC BOOTSTRAPPING	0
Regularizing nested Monte Carlo Sobol' index estimators to balance the trade-off between explorations and repetitions in global sensitivity analysis of stochastic models	0
	0
QUANTIFYING UNCERTAIN SYSTEM OUTPUTS VIA THE MULTI-LEVEL MONTE CARLO METHOD-DISTRIBUTION AND ROBUSTNESS MEASURES	0
DERIVATIVE-BASED SHAPLEY VALUE FOR GLOBAL SENSITIVITY ANALYSIS AND MACHINE LEARNING EXPLAINABILITY	0
MAXIMIZING REGIONAL SENSITIVITY ANALYSIS INDICES TO FIND SENSITIVE MODEL BEHAVIORS	0
HIGH-DIMENSIONAL STOCHASTIC DESIGN OPTIMIZATION UNDER DEPENDENT RANDOM VARIABLES BY A DIMENSIONALLY DECOMPOSED GENERALIZED POLYNOMIAL CHAOS EXPANSION	0
	0
GLOBAL SENSITIVITY ANALYSIS OF RARE EVENT PROBABILITIES USING SUBSET SIMULATION AND POLYNOMIAL CHAOS EXPANSIONS	0
ANALYSIS OF THE CHALLENGES IN DEVELOPING SAMPLE-BASED MULTIFIDELITY ESTIMATORS FOR NONDETERMINISTIC MODELS	0
NESTED OPTIMAL UNCERTAINTY QUANTIFICATION FOR AN EFFICIENT INCORPORATION OF RANDOM FIELDS-APPLICATION TO SHEET METAL FORMING	0
MORE POWERFUL HSIC-BASED INDEPENDENCE TESTS, EXTENSION TO SPACE-FILLING DESIGNS AND FUNCTIONAL DATA	0
SOBOL' SENSITIVITY INDICES-A MACHINE LEARNING APPROACH USING THE DYNAMIC ADAPTIVE VARIANCES ESTIMATOR WITH GIVEN DATA	0
Quasi-Monte Carlo sparse grid Galerkin finite element methods for linear elasticity equations with uncertainties	0
NON-INTRUSIVE SURROGATE MODELLING USING SPARSE RANDOM FEATURES WITH APPLICATIONS IN CRASHWORTHINESS ANALYSIS	0
SOLVING STOCHASTIC INVERSE PROBLEMS FOR CFD USING DATA-CONSISTENT INVERSION AND AN ADAPTIVE STOCHASTIC COLLOCATION METHOD	0
A BAYESIAN CALIBRATION FRAMEWORK WITH EMBEDDED MODEL ERROR FOR MODEL DIAGNOSTICS	0
HAMILTONIAN MONTE CARLO IN INVERSE PROBLEMS. ILL-CONDITIONING AND MULTIMODALITY	0