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ORCIDSIAM/ASA Journal on Uncertainty Quantification, Volume 6
Volume 6, Number 1, 2018
- Nicolas Bousquet
, Thierry Klein, Vincent Moutoussamy:
Approximation of Limit State Surfaces in Monotonic Monte Carlo Settings, with Applications to Classification. 1-33 - Grace X. Hu, David R. Kuipers, Yong Zeng:
Bayesian Inference via Filtering Equations for Ultrahigh Frequency Data (I): Model and Estimation. 34-60 - Grace X. Hu, David R. Kuipers, Yong Zeng:
Bayesian Inference via Filtering Equations for Ultrahigh Frequency Data (II): Model Selection. 61-86 - Marta D'Elia, H. Carter Edwards, Jonathan J. Hu, Eric T. Phipps, Sivasankaran Rajamanickam:
Ensemble Grouping Strategies for Embedded Stochastic Collocation Methods Applied to Anisotropic Diffusion Problems. 87-117 - Donsub Rim, Scott Moe, Randall J. LeVeque:
Transport Reversal for Model Reduction of Hyperbolic Partial Differential Equations. 118-150 - Guillaume Damblin, Pierre Barbillon, Merlin Keller, Alberto Pasanisi, Eric C. Parent:
Adaptive Numerical Designs for the Calibration of Computer Codes. 151-179 - David A. Barajas-Solano, Alexandre M. Tartakovsky:
Probability and Cumulative Density Function Methods for the Stochastic Advection-Reaction Equation. 180-212 - Clemens Heitzinger, Gudmund Pammer, Stefan Rigger:
Cubature Formulas for Multisymmetric Functions and Applications to Stochastic Partial Differential Equations. 213-242 - Alex Bespalov, Leonardo Rocchi:
Efficient Adaptive Algorithms for Elliptic PDEs with Random Data. 243-272 - Ramakrishna Tipireddy, Panos Stinis, Alexandre M. Tartakovsky:
Stochastic Basis Adaptation and Spatial Domain Decomposition for Partial Differential Equations with Random Coefficients. 273-301 - Erkan Nane, Nguyen Huy Tuan:
Approximate Solutions of Inverse Problems for Nonlinear Space Fractional Diffusion Equations with Randomly Perturbed Data. 302-338 - Patrick R. Conrad, Andrew D. Davis, Youssef M. Marzouk, Natesh S. Pillai, Aaron Smith:
Parallel Local Approximation MCMC for Expensive Models. 339-373 - Kookjin Lee, Kevin Carlberg, Howard C. Elman:
Stochastic Least-Squares Petrov-Galerkin Method for Parameterized Linear Systems. 374-396 - Emanuele Borgonovo, Max D. Morris, Elmar Plischke:
Functional ANOVA with Multiple Distributions: Implications for the Sensitivity Analysis of Computer Experiments. 397-427
Volume 6, Number 2, 2018
- Arun Hegde, Wenyu Li, James Oreluk, Andrew K. Packard, Michael Frenklach:
Consistency Analysis for Massively Inconsistent Datasets in Bound-to-Bound Data Collaboration. 429-456 - Rebecca E. Morrison, Todd A. Oliver, Robert D. Moser:
Representing Model Inadequacy: A Stochastic Operator Approach. 457-496 - Benjamin Haaland, Wenjia Wang, Vaibhav Maheshwari:
A Framework for Controlling Sources of Inaccuracy in Gaussian Process Emulation of Deterministic Computer Experiments. 497-521 - Fabrice Gamboa, Thierry Klein, Agnès Lagnoux:
Sensitivity Analysis Based on Cramér-von Mises Distance. 522-548 - Leifur Thorbergsson, Giles Hooker:
Experimental Design for Partially Observed Markov Decision Processes. 549-567 - Andrea L. Bertozzi, Xiyang Luo, Andrew M. Stuart, Konstantinos C. Zygalakis:
Uncertainty Quantification in Graph-Based Classification of High Dimensional Data. 568-595 - Joseph Durante, Raj Patel, Warren B. Powell:
Scenario Generation Methods that Replicate Crossing Times in Spatially Distributed Stochastic Systems. 596-626 - Xu He, Peter Chien:
On the Instability Issue of Gradient-Enhanced Gaussian Process Emulators for Computer Experiments. 627-644 - Matthew D. Parno, Youssef M. Marzouk:
Transport Map Accelerated Markov Chain Monte Carlo. 645-682 - Elizabeth Qian, Benjamin Peherstorfer, Daniel O'Malley, Velimir V. Vesselinov, Karen Willcox:
Multifidelity Monte Carlo Estimation of Variance and Sensitivity Indices. 683-706 - Robert N. Gantner, M. D. Peters:
Higher-Order Quasi-Monte Carlo for Bayesian Shape Inversion. 707-736 - Benjamin Peherstorfer, Boris Kramer, Karen Willcox:
Multifidelity Preconditioning of the Cross-Entropy Method for Rare Event Simulation and Failure Probability Estimation. 737-761 - Alexandros Beskos, Ajay Jasra, Kody J. H. Law, Youssef M. Marzouk, Yan Zhou:
Multilevel Sequential Monte Carlo with Dimension-Independent Likelihood-Informed Proposals. 762-786 - Drew P. Kouri, Thomas M. Surowiec:
Existence and Optimality Conditions for Risk-Averse PDE-Constrained Optimization. 787-815 - Sharif Rahman:
Mathematical Properties of Polynomial Dimensional Decomposition. 816-844 - Jeremie Houssineau, Adrian N. Bishop:
Smoothing and Filtering with a Class of Outer Measures. 845-866 - Daniel Sanz-Alonso:
Importance Sampling and Necessary Sample Size: An Information Theory Approach. 867-879 - Gal Shulkind, Lior Horesh, Haim Avron:
Experimental Design for Nonparametric Correction of Misspecified Dynamical Models. 880-906 - Xun Huan, Cosmin Safta, Khachik Sargsyan, Zachary P. Vane, Guilhem Lacaze, Joseph C. Oefelein, Habib N. Najm:
Compressive Sensing with Cross-Validation and Stop-Sampling for Sparse Polynomial Chaos Expansions. 907-936 - Assyr Abdulle, Ibrahim Almuslimani, Gilles Vilmart:
Optimal Explicit Stabilized Integrator of Weak Order 1 for Stiff and Ergodic Stochastic Differential Equations. 937-964 - Peter Benner, Yue Qiu, Martin Stoll:
Low-Rank Eigenvector Compression of Posterior Covariance Matrices for Linear Gaussian Inverse Problems. 965-989
Volume 6, Number 3, 2018
- Sébastien Marmin, David Ginsbourger, Jean Baccou, Jacques Liandrat:
Warped Gaussian Processes and Derivative-Based Sequential Designs for Functions with Heterogeneous Variations. 991-1018 - Clemens Heitzinger, Michael Leumüller, Gudmund Pammer, Stefan Rigger:
Existence, Uniqueness, and a Comparison of Nonintrusive Methods for the Stochastic Nonlinear Poisson-Boltzmann Equation. 1019-1042 - Gilles Blanchard, Marc Hoffmann, Markus Reiß:
Optimal Adaptation for Early Stopping in Statistical Inverse Problems. 1043-1075 - D. Andrew Brown, Arvind K. Saibaba, Sarah Vallélian:
Low-Rank Independence Samplers in Hierarchical Bayesian Inverse Problems. 1076-1100 - Peter Binev, Albert Cohen, Olga Mula, James A. Nichols:
Greedy Algorithms for Optimal Measurements Selection in State Estimation Using Reduced Models. 1101-1126 - Jehanzeb Hameed Chaudhry, Nathanial Burch, Donald J. Estep:
Efficient Distribution Estimation and Uncertainty Quantification for Elliptic Problems on Domains with Stochastic Boundaries. 1127-1150 - Ksenia N. Kyzyurova, James O. Berger, Robert L. Wolpert:
Coupling Computer Models through Linking Their Statistical Emulators. 1151-1171 - Rafael Ballester-Ripoll, Enrique G. Paredes, Renato Pajarola:
Tensor Algorithms for Advanced Sensitivity Metrics. 1172-1197 - Nan Chen, Andrew J. Majda, Xin T. Tong:
Rigorous Analysis for Efficient Statistically Accurate Algorithms for Solving Fokker-Planck Equations in Large Dimensions. 1198-1223 - Andrés F. López-Lopera, François Bachoc, Nicolas Durrande, Olivier Roustant:
Finite-Dimensional Gaussian Approximation with Linear Inequality Constraints. 1224-1255 - Sebastian Krumscheid, Fabio Nobile:
Multilevel Monte Carlo Approximation of Functions. 1256-1293
Volume 6, Number 4, 2018
- Dimitris Kamilis, Nick Polydorides:
Uncertainty Quantification for Low-Frequency, Time-Harmonic Maxwell Equations with Stochastic Conductivity Models. 1295-1334 - Colin Grudzien, Alberto Carrassi, Marc Bocquet:
Asymptotic Forecast Uncertainty and the Unstable Subspace in the Presence of Additive Model Error. 1335-1363 - Eric Joseph Hall, Markos A. Katsoulakis:
Robust Information Divergences for Model-Form Uncertainty Arising from Sparse Data in Random PDE. 1364-1394 - Matthias Heinkenschloss, Boris Kramer, Timur Takhtaganov, Karen Willcox:
Conditional-Value-at-Risk Estimation via Reduced-Order Models. 1395-1423 - Ben Adcock, Anyi Bao, John D. Jakeman, Akil Narayan:
Compressed Sensing with Sparse Corruptions: Fault-Tolerant Sparse Collocation Approximations. 1424-1453 - Michael B. Giles, Francisco Bernal:
Multilevel Estimation of Expected Exit Times and Other Functionals of Stopped Diffusions. 1454-1474 - Davide Torlo, Francesco Ballarin, Gianluigi Rozza:
Stabilized Weighted Reduced Basis Methods for Parametrized Advection Dominated Problems with Random Inputs. 1475-1502 - Donsub Rim, Kyle T. Mandli:
Displacement Interpolation Using Monotone Rearrangement. 1503-1531 - Xiu Yang, Weixuan Li, Alexandre M. Tartakovsky:
Sliced-Inverse-Regression-Aided Rotated Compressive Sensing Method for Uncertainty Quantification. 1532-1554 - Mengyang Gu, Long Wang:
Scaled Gaussian Stochastic Process for Computer Model Calibration and Prediction. 1555-1583 - Max D. Morris:
Decomposing Functional Model Inputs for Variance-Based Sensitivity Analysis. 1584-1599 - Han Cheng Lie, Timothy John Sullivan, Aretha L. Teckentrup:
Random Forward Models and Log-Likelihoods in Bayesian Inverse Problems. 1600-1629 - Matteo Croci, Michael B. Giles, Marie E. Rognes, Patrick E. Farrell:
Efficient White Noise Sampling and Coupling for Multilevel Monte Carlo with Nonnested Meshes. 1630-1655 - Ana Djurdjevac, Charles M. Elliott, Ralf Kornhuber, Thomas Ranner:
Evolving Surface Finite Element Methods for Random Advection-Diffusion Equations. 1656-1684 - Arindam Fadikar, Dave Higdon, Jiangzhuo Chen, Bryan L. Lewis, Srinivasan Venkatramanan, Madhav V. Marathe:
Calibrating a Stochastic, Agent-Based Model Using Quantile-Based Emulation. 1685-1706 - Andrea Barth, Andreas Stein:
A Study of Elliptic Partial Differential Equations with Jump Diffusion Coefficients. 1707-1743 - Kookjin Lee, Bedrich Sousedík:
Inexact Methods for Symmetric Stochastic Eigenvalue Problems. 1744-1776
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