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ORCIDSIAM/ASA Journal on Uncertainty Quantification, Volume 10
Volume 10, Number 1, March 2022
- Saumya Bhatnagar, Won Chang
, Seonjin Kim, Jiali Wang:
Computer Model Calibration with Time Series Data Using Deep Learning and Quantile Regression. 1-26 - John Barr, Herschel Rabitz:
A Generalized Kernel Method for Global Sensitivity Analysis. 27-54 - Louis Sharrock, Nikolas Kantas:
Joint Online Parameter Estimation and Optimal Sensor Placement for the Partially Observed Stochastic Advection-Diffusion Equation. 55-95 - Hà Quang Minh:
Finite Sample Approximations of Exact and Entropic Wasserstein Distances Between Covariance Operators and Gaussian Processes. 96-124 - Devin Francom, Bruno Sansó, Ana Kupresanin:
Landmark-Warped Emulators for Models with Misaligned Functional Response. 125-150 - Teresa Portone, Robert D. Moser:
Bayesian Inference of an Uncertain Generalized Diffusion Operator. 151-178 - Randolf Altmeyer, Till Bretschneider, Josef Janák, Markus Reiß:
Parameter Estimation in an SPDE Model for Cell Repolarization. 179-199 - Michael B. Giles, Oliver Sheridan-Methven:
Analysis of Nested Multilevel Monte Carlo Using Approximate Normal Random Variables. 200-226 - Albert Cohen, Wolfgang Dahmen, Olga Mula, James A. Nichols:
Nonlinear Reduced Models for State and Parameter Estimation. 227-267 - Rachel H. Oughton, Michael Goldstein, John C. P. Hemmings:
Intermediate Variable Emulation: Using Internal Processes in Simulators to Build More Informative Emulators. 268-293 - Hossein Mohammadi, Peter G. Challenor, Daniel B. Williamson, Marc Goodfellow:
Cross-Validation-based Adaptive Sampling for Gaussian Process Models. 294-316 - Fabian Wagner, Iason Papaioannou, Elisabeth Ullmann:
The Ensemble Kalman Filter for Rare Event Estimation. 317-349 - Amy L. Wilson, Michael Goldstein, Chris J. Dent:
Varying Coefficient Models and Design Choice for Bayes Linear Emulation of Complex Computer Models with Limited Model Evaluations. 350-378 - Baptiste Broto, François Bachoc, Laura Clouvel, Jean-Marc Martinez:
Block-Diagonal Covariance Estimation and Application to the Shapley Effects in Sensitivity Analysis. 379-403 - Sharif Rahman, Ramin Jahanbin:
A Spline Dimensional Decomposition for Uncertainty Quantification in High Dimensions. 404-438 - Robert Sawko, Malgorzata J. Zimon:
Effective Generation of Compressed Stationary Gaussian Fields. 439-452 - Charles-Edouard Bréhier, David Cohen:
Strong Rates of Convergence of a Splitting Scheme for Schrödinger Equations with Nonlocal Interaction Cubic Nonlinearity and White Noise Dispersion. 453-480 - Jialei Chen, Zhehui Chen, Chuck Zhang, C. F. Jeff Wu:
APIK: Active Physics-Informed Kriging Model with Partial Differential Equations. 481-506 - El Houcine Bergou, Youssef Diouane, Vyacheslav Kungurtsev, Clément W. Royer:
A Stochastic Levenberg-Marquardt Method Using Random Models with Complexity Results. 507-536 - Oliver G. Ernst, Alois Pichler, Björn Sprungk:
Wasserstein Sensitivity of Risk and Uncertainty Propagation. 915-948 - Peijun Li, Xu Wang:
An Inverse Random Source Problem for the Biharmonic Wave Equation. 949-974 - Laura Scarabosio:
Deep Neural Network Surrogates for Nonsmooth Quantities of Interest in Shape Uncertainty Quantification. 975-1011 - Yuchen He, Namjoon Suh, Xiaoming Huo, Sung Ha Kang, Yajun Mei:
Asymptotic Theory of \(\boldsymbol \ell _1\) -Regularized PDE Identification from a Single Noisy Trajectory. 1012-1036 - Kévin Elie-Dit-Cosaque, Véronique Maume-Deschamps:
Goal-Oriented Shapley Effects with Special Attention to the Quantile-Oriented Case. 1037-1069 - Kody J. H. Law, Vitaly Zankin:
Sparse Online Variational Bayesian Regression. 1070-1100 - Bedrich Sousedík, Kookjin Lee:
Stochastic Galerkin Methods for Linear Stability Analysis of Systems with Parametric Uncertainty. 1101-1129 - Hamza M. Ruzayqat, Aimad Er-Raiy, Alexandros Beskos, Dan Crisan, Ajay Jasra, Nikolas Kantas:
A Lagged Particle Filter for Stable Filtering of Certain High-Dimensional State-Space Models. 1130-1161 - Paul Hagemann, Johannes Hertrich, Gabriele Steidl:
Stochastic Normalizing Flows for Inverse Problems: A Markov Chains Viewpoint. 1162-1190 - Paul B. Rohrbach, Sergey Dolgov, Lars Grasedyck, Robert Scheichl:
Rank Bounds for Approximating Gaussian Densities in the Tensor-Train Format. 1191-1224 - Victor Churchill, Anne Gelb:
Sampling-based Spotlight SAR Image Reconstruction from Phase History Data for Speckle Reduction and Uncertainty Quantification. 1225-1249 - Trung Pham, Alex A. Gorodetsky:
Ensemble Approximate Control Variate Estimators: Applications to MultiFidelity Importance Sampling. 1250-1292 - Felipe Uribe, Johnathan M. Bardsley, Yiqiu Dong, Per Christian Hansen, Nicolai André Brogaard Riis:
A Hybrid Gibbs Sampler for Edge-Preserving Tomographic Reconstruction with Uncertain View Angles. 1293-1320 - Drew P. Kouri, Thomas M. Surowiec:
Corrigendum: "Existence and Optimality Conditions for Risk-Averse PDE-Constrained Optimization". 1321-1322
Volume 10, Number 2, June 2022
- Matthias Katzfuss, Joseph Guinness, Earl Lawrence:
Scaled Vecchia Approximation for Fast Computer-Model Emulation. 537-554 - Hassan Arbabi, Themistoklis P. Sapsis:
Generative Stochastic Modeling of Strongly Nonlinear Flows with Non-Gaussian Statistics. 555-583 - Neil K. Chada, Ajay Jasra, Fangyuan Yu:
Multilevel Ensemble Kalman-Bucy Filters. 584-618 - Wenjia Wang, Xiaowei Yue, Benjamin Haaland, C. F. Jeff Wu:
Gaussian Processes with Input Location Error and Applications to the Composite Parts Assembly Process. 619-650 - Josef Dick, Marcello Longo, Christoph Schwab:
Extrapolated Polynomial Lattice Rule Integration in Computational Uncertainty Quantification. 651-686 - Drew P. Kouri, John D. Jakeman, J. Gabriel Huerta:
Risk-Adapted Optimal Experimental Design. 687-716 - James M. Salter, Daniel B. Williamson, Lauren J. Gregoire, Tamsin L. Edwards:
Quantifying Spatio-Temporal Boundary Condition Uncertainty for the North American Deglaciation. 717-744 - Jiahui Zhang, Anne Gelb, Theresa Scarnati:
Empirical Bayesian Inference Using a Support Informed Prior. 745-774 - Alexander M. G. Cox, Simon C. Harris, Andreas E. Kyprianou, Minmin Wang:
Monte Carlo Methods for the Neutron Transport Equation. 775-825
Volume 10, Number 3, September 2022
- Pratik Patil, Mikael Kuusela, Jonathan Hobbs:
Objective Frequentist Uncertainty Quantification for Atmospheric \(\mathrm{CO}_2\) Retrievals. 827-859 - Michael Lindsey, Jonathan Weare, Anna Zhang:
Ensemble Markov Chain Monte Carlo with Teleporting Walkers. 860-885 - Shay Gilpin, Tomoko Matsuo, Stephen E. Cohn:
Continuum Covariance Propagation for Understanding Variance Loss in Advective Systems. 886-914
Volume 10, Number 4, December 2022
- Daniel Sanz-Alonso, Ruiyi Yang:
Finite Element Representations of Gaussian Processes: Balancing Numerical and Statistical Accuracy. 1323-1349 - Florian Bourgey, Emmanuel Gobet, Clément Rey:
A Comparative Study of Polynomial-Type Chaos Expansions for Indicator Functions. 1350-1383 - Nan Chen, Quanling Deng, Samuel N. Stechmann:
Superfloe Parameterization with Physics Constraints for Uncertainty Quantification of Sea Ice Floes. 1384-1409 - Mengqi Hu, Yifei Lou, Xiu Yang:
A General Framework of Rotational Sparse Approximation in Uncertainty Quantification. 1410-1434 - Mengyang Gu, Fangzheng Xie, Long Wang:
A Theoretical Framework of the Scaled Gaussian Stochastic Process in Prediction and Calibration. 1435-1460 - Panagiota Birmpa, Jinchao Feng, Markos A. Katsoulakis, Luc Rey-Bellet:
Model Uncertainty and Correctability for Directed Graphical Models. 1461-1512 - Yifei Wang, Peng Chen, Wuchen Li:
Projected Wasserstein Gradient Descent for High-Dimensional Bayesian Inference. 1513-1532 - Shiv Agrawal, Hwanwoo Kim, Daniel Sanz-Alonso, Alexander Strang:
A Variational Inference Approach to Inverse Problems with Gamma Hyperpriors. 1533-1559 - Ömer Deniz Akyildiz, Connor Duffin, Sotirios Sabanis, Mark Girolami:
Statistical Finite Elements via Langevin Dynamics. 1560-1585 - Thierry Klein, Nicolas Peteilh, Paul Rochet:
Test Comparison for Sobol Indices over Nested Sets of Variables. 1586-1600 - Marcus J. Grote, Simon Michel, Fabio Nobile:
Uncertainty Quantification by Multilevel Monte Carlo and Local Time-Stepping for Wave Propagation. 1601-1628 - Zilong Zou, Drew P. Kouri, Wilkins Aquino:
A Locally Adapted Reduced-Basis Method for Solving Risk-Averse PDE-Constrained Optimization Problems. 1629-1651 - Yan Wang:
Penalized Projected Kernel Calibration for Computer Models. 1652-1683 - Shiwei Lan, Shuyi Li, Babak Shahbaba:
Scaling Up Bayesian Uncertainty Quantification for Inverse Problems Using Deep Neural Networks. 1684-1713 - Moyan Li, Raed Kontar:
On Negative Transfer and Structure of Latent Functions in Multioutput Gaussian Processes. 1714-1732 - Chih-Li Sung, Beau David Barber, Berkley J. Walker:
Calibration of Inexact Computer Models with Heteroscedastic Errors. 1733-1752 - Tobias Jahnke, Benny Stein:
A Multilevel Stochastic Collocation Method for Schrödinger Equations with a Random Potential. 1753-1780
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