OOIR: Observatory of International Research

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 2020-04-01 to 2024-04-01.)

Article	Citations
DEEP LEARNING OF PARAMETERIZED EQUATIONS WITH APPLICATIONS TO UNCERTAINTY QUANTIFICATION	22
STOCHASTIC SPECTRAL EMBEDDING	21
MANIFOLD LEARNING-BASED POLYNOMIAL CHAOS EXPANSIONS FOR HIGH-DIMENSIONAL SURROGATE MODELS	15
A COMPREHENSIVE COMPARISON OF TOTAL-ORDER ESTIMATORS FOR GLOBAL SENSITIVITY ANALYSIS	14
AUTOMATIC SELECTION OF BASIS-ADAPTIVE SPARSE POLYNOMIAL CHAOS EXPANSIONS FOR ENGINEERING APPLICATIONS	13
COMPUTATION OF SOBOL INDICES IN GLOBAL SENSITIVITY ANALYSIS FROM SMALL DATA SETS BY PROBABILISTIC LEARNING ON MANIFOLDS	10
EMBEDDED MULTILEVEL MONTE CARLO FOR UNCERTAINTY QUANTIFICATION IN RANDOM DOMAINS	9
EXPLICIT ESTIMATION OF DERIVATIVES FROM DATA AND DIFFERENTIAL EQUATIONS BY GAUSSIAN PROCESS REGRESSION	6
ACCRUE: ACCURATE AND RELIABLE UNCERTAINTY ESTIMATE IN DETERMINISTIC MODELS	6
DYNAMICAL LOW-RANK APPROXIMATION FOR BURGERS' EQUATION WITH UNCERTAINTY	6
ISOGEOMETRIC METHODS FOR KARHUNEN-LOEVE REPRESENTATION OF RANDOM FIELDS ON ARBITRARY MULTIPATCH DOMAINS	5
ERROR ESTIMATE OF A BIFIDELITY METHOD FOR KINETIC EQUATIONS WITH RANDOM PARAMETERS AND MULTIPLE SCALES	5
MULTILEVEL QUASI-MONTE CARLO FOR INTERVAL ANALYSIS	5
AN EFFICIENT COMPUTATIONAL METHOD FOR PARAMETER IDENTIFICATION IN THE CONTEXT OF RANDOM SET THEORY VIA BAYESIAN INVERSION	4
MULTI-INDEX SEQUENTIAL MONTE CARLO METHODS FOR PARTIALLY OBSERVED STOCHASTIC PARTIAL DIFFERENTIAL EQUATIONS	4
EXPLORATION OF MULTIFIDELITY UQ SAMPLING STRATEGIES FOR COMPUTER NETWORK APPLICATIONS	3
A FULLY BAYESIAN GRADIENT-FREE SUPERVISED DIMENSION REDUCTION METHOD USING GAUSSIAN PROCESSES	3
MEAN-FIELD CONTROL VARIATE METHODS FOR KINETIC EQUATIONS WITH UNCERTAINTIES AND APPLICATIONS TO SOCIOECONOMIC SCIENCES	3
DEALING WITH INCONSISTENT MEASUREMENTS IN INVERSE PROBLEMS: SET-BASED APPROACH	3
LEARNING HIGH-DIMENSIONAL PROBABILITY DISTRIBUTIONS USING TREE TENSOR NETWORKS	3
SHAPLEY EFFECT ESTIMATION IN RELIABILITY-ORIENTED SENSITIVITY ANALYSIS WITH CORRELATED INPUTS BY IMPORTANCE SAMPLING	3
ADAPTIVE STRATIFIED SAMPLING FOR NONSMOOTH PROBLEMS	3
METHOD FOR THE ANALYSIS OF EPISTEMIC AND ALEATORY UNCERTAINTIES FOR A RELIABLE EVALUATION OF FAILURE OF ENGINEERING STRUCTURES	3
PARAMETER ESTIMATION OF STOCHASTIC CHAOTIC SYSTEMS	2
STABLE LIKELIHOOD COMPUTATION FOR MACHINE LEARNING OF LINEAR DIFFERENTIAL OPERATORS WITH GAUSSIAN PROCESSES	2

QUANTIFYING UNCERTAIN SYSTEM OUTPUTS VIA THE MULTI-LEVEL MONTE CARLO METHOD-DISTRIBUTION AND ROBUSTNESS MEASURES	2
QUANTIFICATION AND PROPAGATION OF MODEL-FORM UNCERTAINTIES IN RANS TURBULENCE MODELING VIA INTRUSIVE POLYNOMIAL CHAOS	2
MIXED COVARIANCE FUNCTION KRIGING MODEL FOR UNCERTAINTY QUANTIFICATION	2
STOCHASTIC POLYNOMIAL CHAOS EXPANSIONS TO EMULATE STOCHASTIC SIMULATORS	2
EFFICIENT APPROXIMATION OF HIGH-DIMENSIONAL EXPONENTIALS BY TENSOR NETWORKS	2
HIGH-DIMENSIONAL STOCHASTIC DESIGN OPTIMIZATION UNDER DEPENDENT RANDOM VARIABLES BY A DIMENSIONALLY DECOMPOSED GENERALIZED POLYNOMIAL CHAOS EXPANSION	2
ROBUST IMPORTANCE SAMPLING FOR BAYESIAN MODEL CALIBRATION WITH SPATIOTEMPORAL DATA	2
AdaAnn: ADAPTIVE ANNEALING SCHEDULER FOR PROBABILITY DENSITY APPROXIMATION	2
KERNEL OPTIMIZATION FOR LOW-RANK MULTIFIDELITY ALGORITHMS	2