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A Fast and Scalable Method for A-Optimal Design of Experiments for Infinite-dimensional Bayesian Nonlinear Inverse Problems

SIAM journal on scientific computing, 2016-01, Vol.38 (1), p.A243-A272

2016

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Exposed soil and mineral map of the Australian continent revealing the land at its barest

Nature communications, 2019-11, Vol.10 (1), p.5297-11, Article 5297

2019

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p4est: SCALABLE ALGORITHMS FOR PARALLEL ADAPTIVE MESH REFINEMENT ON FORESTS OF OCTREES

SIAM journal on scientific computing, 2011-01, Vol.33 (3-4), p.1103-1133

2011

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On Bayesian A- and D-Optimal Experimental Designs in Infinite Dimensions

Bayesian analysis, 2016-09, Vol.11 (3)

2016

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Recursive Algorithms for Distributed Forests of Octrees

SIAM journal on scientific computing, 2015-01, Vol.37 (5), p.C497-C531

2015

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Dynamics of Plate Tectonics and Mantle Flow: From Local to Global Scales

Science (American Association for the Advancement of Science), 2010-08, Vol.329 (5995), p.1033-1038

2010

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Learning physics-based models from data: perspectives from inverse problems and model reduction

Acta numerica, 2021-05, Vol.30, p.445-554

2021

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Towards adjoint-based inversion for rheological parameters in nonlinear viscous mantle flow

Physics of the earth and planetary interiors, 2014-09, Vol.234, p.23-34

2014

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An inexact Gauss-Newton method for inversion of basal sliding and rheology parameters in a nonlinear Stokes ice sheet model

Journal of glaciology, 2012-01, Vol.58 (211), p.889-903

2012

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Stein Variational Reduced Basis Bayesian Inversion

SIAM journal on scientific computing, 2021-01, Vol.43 (2), p.A1163-A1193

2021

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Limits of use of social media for monitoring biosecurity events

PloS one, 2017-02, Vol.12 (2), p.e0172457-e0172457

2017

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Taylor approximation and variance reduction for PDE-constrained optimal control under uncertainty

Journal of computational physics, 2019-05, Vol.385 (C), p.163-186

2019

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Interior over-penalized enriched Galerkin methods for second order elliptic equations

Computers & mathematics with applications (1987), 2023-12, Vol.152 (C), p.102-111

2023

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Scalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the Antarctic ice sheet

Journal of computational physics, 2015-09, Vol.296 (C), p.348-368

2015

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Constructively well-posed approximation methods with unity inf--sup and continuity constants for partial differential equations

Mathematics of computation, 2013-10, Vol.82 (284), p.1923-1952

2013

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Hessian-based adaptive sparse quadrature for infinite-dimensional Bayesian inverse problems

Computer methods in applied mechanics and engineering, 2017-12, Vol.327 (C), p.147-172

2017

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hIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems Governed by PDEs: Part I: Deterministic Inversion and Linearized Bayesian Inference

ACM transactions on mathematical software, 2021-04, Vol.47 (2), p.1-34

2021

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Slab stress and strain rate as constraints on global mantle flow

Geophysical research letters, 2010-11, Vol.37 (22), p.np-n/a

2010

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Optimal design of acoustic metamaterial cloaks under uncertainty

Journal of computational physics, 2021-04, Vol.431 (C), p.110114, Article 110114

2021

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Bayesian inference of heterogeneous epidemic models: Application to COVID-19 spread accounting for long-term care facilities

Computer methods in applied mechanics and engineering, 2021-11, Vol.385 (C), p.114020-114020, Article 114020

2021

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Resin percolation and intimate contact in fast processing of thermoplastic composites

Composites. Part A, Applied science and manufacturing, 2024-07, Vol.182, p.108145, Article 108145

2024

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A Computational Framework for Infinite-Dimensional Bayesian Inverse Problems, Part II: Stochastic Newton MCMC with Application to Ice Sheet Flow Inverse Problems

SIAM journal on scientific computing, 2014-01, Vol.36 (4), p.A1525-A1555

2014

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An Offline-Online Decomposition Method for Efficient Linear Bayesian Goal-Oriented Optimal Experimental Design: Application to Optimal Sensor Placement

SIAM journal on scientific computing, 2023-01, Vol.45 (1), p.B57-B77

2023

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Parameter and State Model Reduction for Large-Scale Statistical Inverse Problems

SIAM journal on scientific computing, 2010-01, Vol.32 (5), p.2523-2542

2010

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Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning

Journal of computational physics, 2024-01, Vol.496 (C), p.112555, Article 112555

2024

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A Fast and Scalable Method for A-Optimal Design of Experiments for Infinite-dimensional Bayesian Nonlinear Inverse Problems

Exposed soil and mineral map of the Australian continent revealing the land at its barest

p4est: SCALABLE ALGORITHMS FOR PARALLEL ADAPTIVE MESH REFINEMENT ON FORESTS OF OCTREES

On Bayesian A- and D-Optimal Experimental Designs in Infinite Dimensions

Recursive Algorithms for Distributed Forests of Octrees

Dynamics of Plate Tectonics and Mantle Flow: From Local to Global Scales

Learning physics-based models from data: perspectives from inverse problems and model reduction

Towards adjoint-based inversion for rheological parameters in nonlinear viscous mantle flow

An inexact Gauss-Newton method for inversion of basal sliding and rheology parameters in a nonlinear Stokes ice sheet model

Stein Variational Reduced Basis Bayesian Inversion

Limits of use of social media for monitoring biosecurity events

Taylor approximation and variance reduction for PDE-constrained optimal control under uncertainty

Interior over-penalized enriched Galerkin methods for second order elliptic equations

Scalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the Antarctic ice sheet

Constructively well-posed approximation methods with unity inf--sup and continuity constants for partial differential equations

Hessian-based adaptive sparse quadrature for infinite-dimensional Bayesian inverse problems

hIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems Governed by PDEs: Part I: Deterministic Inversion and Linearized Bayesian Inference

Slab stress and strain rate as constraints on global mantle flow

Optimal design of acoustic metamaterial cloaks under uncertainty

Bayesian inference of heterogeneous epidemic models: Application to COVID-19 spread accounting for long-term care facilities

Resin percolation and intimate contact in fast processing of thermoplastic composites

A Computational Framework for Infinite-Dimensional Bayesian Inverse Problems, Part II: Stochastic Newton MCMC with Application to Ice Sheet Flow Inverse Problems

An Offline-Online Decomposition Method for Efficient Linear Bayesian Goal-Oriented Optimal Experimental Design: Application to Optimal Sensor Placement

Parameter and State Model Reduction for Large-Scale Statistical Inverse Problems

Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning

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