International Journal for Uncertainty Quantification

Papers
(The TQCC of International Journal for 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 2021-05-01 to 2025-05-01.)
ArticleCitations
COMPUTATIONAL CHALLENGES IN SAMPLING AND REPRESENTATION OF UNCERTAIN REACTION KINETICS IN LARGE DIMENSIONS25
Bayesian³ Active learning for regularized arbitrary multi-element polynomial chaos using information theory21
SENSITIVITY ANALYSIS WITH CORRELATED INPUTS: COMPARISON OF INDICES FOR THE LINEAR CASE15
11
CONTROL VARIATE POLYNOMIAL CHAOS: OPTIMAL FUSION OF SAMPLING AND SURROGATES FOR MULTIFIDELITY UNCERTAINTY QUANTIFICATION9
A novel probabilistic transfer learning strategy for polynomial regression8
Uncertainty quantification for deep learning-based schemes for solving high-dimensional backward stochastic differential equations7
MAJORIZATION AS A THEORY FOR UNCERTAINTY7
COVARIANCE ESTIMATION USING h-STATISTICS IN MONTE CARLO AND MULTILEVEL MONTE CARLO METHODS6
5
5
5
Lp CONVERGENCE OF APPROXIMATE MAPS AND PROBABILITY DENSITIES FOR FORWARD AND INVERSE PROBLEMS IN UNCERTAINTY QUANTIFICATION5
4
SENSITIVITY ANALYSES OF A MULTIPHYSICS LONG-TERM CLOGGING MODEL FOR STEAM GENERATORS4
PARALLEL PARTIAL EMULATION IN APPLICATIONS3
MEASURING INPUTS-OUTPUTS ASSOCIATION FOR TIME-DEPENDENT HAZARD MODELS UNDER SAFETY OBJECTIVES USING KERNELS3
LONG SHORT-TERM RELEVANCE LEARNING3
Clustering based multiple anchors high-dimensional model representation3
A FULLY BAYESIAN GRADIENT-FREE SUPERVISED DIMENSION REDUCTION METHOD USING GAUSSIAN PROCESSES3
STRUCTURE-PRESERVING MODEL ORDER REDUCTION OF RANDOM PARAMETRIC LINEAR SYSTEMS VIA REGRESSION3
2
STOCHASTIC GALERKIN METHOD AND PORT-HAMILTONIAN FORM FOR LINEAR FIRST-ORDER ORDINARY DIFFERENTIAL EQUATIONS2
SHAPLEY EFFECT ESTIMATION IN RELIABILITY-ORIENTED SENSITIVITY ANALYSIS WITH CORRELATED INPUTS BY IMPORTANCE SAMPLING2
2
INDEX2
BAYESIAN PARAMETER INFERENCE FOR PARTIALLY OBSERVED DIFFUSIONS USING MULTILEVEL STOCHASTIC RUNGE-KUTTA METHODS2
EFFICIENT CALIBRATION FOR HIGH-DIMENSIONAL COMPUTER MODEL OUTPUT USING BASIS METHODS2
CLOSURE LAW MODEL UNCERTAINTY QUANTIFICATION2
PREFACE: RECENT ADVANCES IN GLOBAL SENSITIVITY ANALYSIS2
GLOBAL SENSITIVITY ANALYSIS USING DERIVATIVE-BASED SPARSE POINCARÉ CHAOS EXPANSIONS2
2
IMPROVING ACCURACY AND COMPUTATIONAL EFFICIENCY OF OPTIMAL DESIGN OF EXPERIMENTS VIA GREEDY BACKWARD APPROACH2
METHOD FOR THE ANALYSIS OF EPISTEMIC AND ALEATORY UNCERTAINTIES FOR A RELIABLE EVALUATION OF FAILURE OF ENGINEERING STRUCTURES2
UNCERTAINTY QUANTIFICATION AND GLOBAL SENSITIVITY ANALYSIS OF SEISMIC FRAGILITY CURVES USING KRIGING2
0.038541078567505