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 2021-09-01 to 2025-09-01.)

Article	Citations
COMPUTATIONAL CHALLENGES IN SAMPLING AND REPRESENTATION OF UNCERTAIN REACTION KINETICS IN LARGE DIMENSIONS	31
	29
BAYESIAN3 ACTIVE LEARNING FOR REGULARIZED ARBITRARY MULTIELEMENT POLYNOMIAL CHAOS USING INFORMATION THEORY	25
SENSITIVITY ANALYSIS WITH CORRELATED INPUTS: COMPARISON OF INDICES FOR THE LINEAR CASE	15
CONTROL VARIATE POLYNOMIAL CHAOS: OPTIMAL FUSION OF SAMPLING AND SURROGATES FOR MULTIFIDELITY UNCERTAINTY QUANTIFICATION	11
UNCERTAINTY QUANTIFICATION FOR DEEP LEARNING-BASED SCHEMES FOR SOLVING HIGH-DIMENSIONAL BACKWARD STOCHASTIC DIFFERENTIAL EQUATIONS	10
COVARIANCE ESTIMATION USING h-STATISTICS IN MONTE CARLO AND MULTILEVEL MONTE CARLO METHODS	7
MAJORIZATION AS A THEORY FOR UNCERTAINTY	7
	7
A NOVEL PROBABILISTIC TRANSFER LEARNING STRATEGY FOR POLYNOMIAL REGRESSION	7
SENSITIVITY ANALYSES OF A MULTIPHYSICS LONG-TERM CLOGGING MODEL FOR STEAM GENERATORS	6
	6
	6
Lp CONVERGENCE OF APPROXIMATE MAPS AND PROBABILITY DENSITIES FOR FORWARD AND INVERSE PROBLEMS IN UNCERTAINTY QUANTIFICATION	5
STRUCTURE-PRESERVING MODEL ORDER REDUCTION OF RANDOM PARAMETRIC LINEAR SYSTEMS VIA REGRESSION	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
	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
LONG SHORT-TERM RELEVANCE LEARNING	3

BAYESIAN PARAMETER INFERENCE FOR PARTIALLY OBSERVED DIFFUSIONS USING MULTILEVEL STOCHASTIC RUNGE-KUTTA METHODS	3
SHAPLEY EFFECT ESTIMATION IN RELIABILITY-ORIENTED SENSITIVITY ANALYSIS WITH CORRELATED INPUTS BY IMPORTANCE SAMPLING	3
GLOBAL SENSITIVITY ANALYSIS USING DERIVATIVE-BASED SPARSE POINCARÉ CHAOS EXPANSIONS	3
	3
	3
UNCERTAINTY QUANTIFICATION AND GLOBAL SENSITIVITY ANALYSIS OF SEISMIC FRAGILITY CURVES USING KRIGING	2
PREFACE: RECENT ADVANCES IN GLOBAL SENSITIVITY ANALYSIS	2
AN ADAPTIVE STRATEGY FOR SEQUENTIAL DESIGNS OF MULTILEVEL COMPUTER EXPERIMENTS	2
	2
	2
STOCHASTIC GALERKIN METHOD AND PORT-HAMILTONIAN FORM FOR LINEAR FIRST-ORDER ORDINARY DIFFERENTIAL EQUATIONS	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
A DOMAIN-DECOMPOSED VAE METHOD FOR BAYESIAN INVERSE PROBLEMS	2
MAXIMUM ENTROPY UNCERTAINTY MODELING AT THE FINITE ELEMENT LEVEL FOR HEATED STRUCTURES	2
EFFICIENT CALIBRATION FOR HIGH-DIMENSIONAL COMPUTER MODEL OUTPUT USING BASIS METHODS	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
	2
A GENERALIZED LIKELIHOOD-WEIGHTED OPTIMAL SAMPLING ALGORITHM FOR RARE-EVENT PROBABILITY QUANTIFICATION	2
	1
AN ENHANCED FRAMEWORK FOR MORRIS BY COMBINING WITH A SEQUENTIAL SAMPLING STRATEGY	1
AUTOMATIC SELECTION OF BASIS-ADAPTIVE SPARSE POLYNOMIAL CHAOS EXPANSIONS FOR ENGINEERING APPLICATIONS	1
MEAN-FIELD CONTROL VARIATE METHODS FOR KINETIC EQUATIONS WITH UNCERTAINTIES AND APPLICATIONS TO SOCIOECONOMIC SCIENCES	1
FEEDBACK CONTROL FOR RANDOM, LINEAR HYPERBOLIC BALANCE LAWS	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
	1
EFFICIENT TREATMENT OF THE MODEL ERROR IN THE CALIBRATION OF COMPUTER CODES: THE COMPLETE MAXIMUM A POSTERIORI METHOD	1
A filtered multilevel Monte Carlo method for estimating the expectation of cell-centered discretized random fields	1
EXTREME LEARNING MACHINES FOR VARIANCE-BASED GLOBAL SENSITIVITY ANALYSIS	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
QUANTIFICATION AND PROPAGATION OF MODEL-FORM UNCERTAINTIES IN RANS TURBULENCE MODELING VIA INTRUSIVE POLYNOMIAL CHAOS	1
DISCREPANCY MODELING FOR MODEL CALIBRATION WITH MULTIVARIATE OUTPUT	1
	1
EFFICIENT APPROXIMATION OF HIGH-DIMENSIONAL EXPONENTIALS BY TENSOR NETWORKS	1
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
REGULARIZING NESTED MONTE CARLO SOBOL' INDEX ESTIMATORS TO BALANCE THE TRADE-OFF BETWEEN EXPLORATIONS AND REPETITIONS IN GLOBAL SENSITIVITY ANALYSIS OF STOCHASTIC MODELS	0
Embedded Nonlocal Operator Regression (ENOR): Quantifying model error in learning nonlocal operators	0
	0
CONTROL VARIATES WITH A DIMENSION REDUCED BAYESIAN MONTE CARLO SAMPLER	0
A DIMENSION-ADAPTIVE COMBINATION TECHNIQUE FOR UNCERTAINTY QUANTIFICATION	0
INDEX, VOLUME 12, 2022	0
STABLE LIKELIHOOD COMPUTATION FOR MACHINE LEARNING OF LINEAR DIFFERENTIAL OPERATORS WITH GAUSSIAN PROCESSES	0
Stein Variational Rare Event Simulation	0
APPLICATION OF GLOBAL SENSITIVITY ANALYSIS FOR IDENTIFICATION OF PROBABILISTIC DESIGN SPACES	0
SENSITIVITY ANALYSIS OF THE INFORMATION GAIN IN INFINITE-DIMENSIONAL BAYESIAN LINEAR INVERSE PROBLEMS	0
SOLVING STOCHASTIC INVERSE PROBLEMS FOR CFD USING DATA-CONSISTENT INVERSION AND AN ADAPTIVE STOCHASTIC COLLOCATION METHOD	0
QUANTIFYING UNCERTAIN SYSTEM OUTPUTS VIA THE MULTI-LEVEL MONTE CARLO METHOD-DISTRIBUTION AND ROBUSTNESS MEASURES	0

STOCHASTIC POLYNOMIAL CHAOS EXPANSIONS TO EMULATE STOCHASTIC SIMULATORS	0
MULTILEVEL MONTE CARLO ESTIMATORS FOR DERIVATIVE-FREE OPTIMIZATION UNDER UNCERTAINTY	0
SOBOL' SENSITIVITY INDICES-A MACHINE LEARNING APPROACH USING THE DYNAMIC ADAPTIVE VARIANCES ESTIMATOR WITH GIVEN DATA	0
HAMILTONIAN MONTE CARLO IN INVERSE PROBLEMS. ILL-CONDITIONING AND MULTIMODALITY	0
	0
DECISION THEORETIC BOOTSTRAPPING	0
	0
QUASI-MONTE CARLO SPARSE GRID GALERKIN FINITE ELEMENT METHODS FOR LINEAR ELASTICITY EQUATIONS WITH UNCERTAINTIES	0
STOCHASTIC GALERKIN METHOD FOR LINEAR FRACTIONAL DIFFERENTIAL EQUATIONS	0
	0
ADAPTIVE STRATIFIED SAMPLING FOR NONSMOOTH PROBLEMS	0
LEARNING HIGH-DIMENSIONAL PROBABILITY DISTRIBUTIONS USING TREE TENSOR NETWORKS	0
MAXIMIZING REGIONAL SENSITIVITY ANALYSIS INDICES TO FIND SENSITIVE MODEL BEHAVIORS	0
	0
	0
DERIVATIVE-BASED SHAPLEY VALUE FOR GLOBAL SENSITIVITY ANALYSIS AND MACHINE LEARNING EXPLAINABILITY	0
BAYESIAN CALIBRATION WITH ADAPTIVE MODEL DISCREPANCY	0
HIGH-DIMENSIONAL STOCHASTIC DESIGN OPTIMIZATION UNDER DEPENDENT RANDOM VARIABLES BY A DIMENSIONALLY DECOMPOSED GENERALIZED POLYNOMIAL CHAOS EXPANSION	0
MORE POWERFUL HSIC-BASED INDEPENDENCE TESTS, EXTENSION TO SPACE-FILLING DESIGNS AND FUNCTIONAL DATA	0
GLOBAL SENSITIVITY ANALYSIS OF RARE EVENT PROBABILITIES USING SUBSET SIMULATION AND POLYNOMIAL CHAOS EXPANSIONS	0
	0
NESTED OPTIMAL UNCERTAINTY QUANTIFICATION FOR AN EFFICIENT INCORPORATION OF RANDOM FIELDS-APPLICATION TO SHEET METAL FORMING	0
NONINTRUSIVE SURROGATE MODELING USING SPARSE RANDOM FEATURES WITH APPLICATIONS IN CRASHWORTHINESS ANALYSIS	0
A BAYESIAN NEURAL NETWORK APPROACH TO MULTI-FIDELITY SURROGATE MODELING	0
DYNAMICAL LOW-RANK APPROXIMATION FOR BURGERS' EQUATION WITH UNCERTAINTY	0
STATISTICAL CLOSURE MODELING FOR REDUCED-ORDER MODELS OF STATIONARY SYSTEMS BY THE ROMES METHOD	0
INDEX, VOLUME 13, 2023	0
UNCERTAINTY QUANTIFICATION OF WATERFLOODING IN OIL RESERVOIRS COMPUTATIONAL SIMULATIONS USING A PROBABILISTIC LEARNING APPROACH	0
PROBABILISTIC UNCERTAINTY PROPAGATION USING GAUSSIAN PROCESS SURROGATES	0
MIXED COVARIANCE FUNCTION KRIGING MODEL FOR UNCERTAINTY QUANTIFICATION	0
HYPERDIFFERENTIAL SENSITIVITY ANALYSIS IN THE CONTEXT OF BAYESIAN INFERENCE APPLIED TO ICE-SHEET PROBLEMS	0
STOCHASTIC GALERKIN FINITE ELEMENT METHOD FOR NONLINEAR ELASTICITY AND APPLICATION TO REINFORCED CONCRETE MEMBERS	0
FIELD SENSITIVITY ANALYSIS OF TURBULENCE MODEL PARAMETERS FOR FLOW OVER A WING	0
A FETI-DP-BASED PARALLEL ALGORITHM FOR SOLVING HIGH DIMENSIONAL STOCHASTIC PDES USING COLLOCATION	0
	0
UNCERTAINTY ANALYSIS FOR EVOLUTION EQUATIONS	0
A STOCHASTIC DOMAIN DECOMPOSITION AND POST-PROCESSING ALGORITHM FOR EPISTEMIC UNCERTAINTY QUANTIFICATION	0
SPARSE TENSOR PRODUCT APPROXIMATION FOR A CLASS OF GENERALIZED METHOD OF MOMENTS ESTIMATORS	0
STABILITY AND CONVERGENCE OF SOLUTIONS TO STOCHASTIC INVERSE PROBLEMS USING APPROXIMATE PROBABILITY DENSITIES	0
ANALYSIS OF THE CHALLENGES IN DEVELOPING SAMPLE-BASED MULTIFIDELITY ESTIMATORS FOR NONDETERMINISTIC MODELS	0
MULTILEVEL QUASI-MONTE CARLO FOR INTERVAL ANALYSIS	0
Bayesian Calibration for Prediction in a Multi-Output Transposition Context	0
HYPER-DIFFERENTIAL SENSITIVITY ANALYSIS FOR NONLINEAR BAYESIAN INVERSE PROBLEMS	0
A BAYESIAN CALIBRATION FRAMEWORK WITH EMBEDDED MODEL ERROR FOR MODEL DIAGNOSTICS	0
VARIANCE-BASED SENSITIVITY OF BAYESIAN INVERSE PROBLEMS TO THE PRIOR DISTRIBUTION	0
EXTREMES OF VECTOR-VALUED PROCESSES BY FINITE DIMENSIONAL MODELS	0
UNCERTAINTY QUANTIFICATION BY GAUSSIAN RANDOM FIELDS FOR POINT-LIKE EMISSIONS FROM SATELLITE OBSERVATIONS	0
AdaAnn: ADAPTIVE ANNEALING SCHEDULER FOR PROBABILITY DENSITY APPROXIMATION	0
LEARNING A CLASS OF STOCHASTIC DIFFERENTIAL EQUATIONS VIA NUMERICS-INFORMED BAYESIAN DENOISING	0
CALCULATING PROBABILITY DENSITIES WITH HOMOTOPY AND APPLICATIONS TO PARTICLE FILTERS	0