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03/21/2023
Scalable Methods for Computing Sharp Extreme Event Probabilities in Infinite-Dimensional Stochastic Systems
We introduce and compare computational techniques for sharp extreme even...
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01/09/2023
Hierarchical off-diagonal low-rank approximation of Hessians in inverse problems, with application to ice sheet model initializaiton
Obtaining lightweight and accurate approximations of Hessian applies in ...
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09/13/2022
Large deviation theory-based adaptive importance sampling for rare events in high dimensions
We propose a method for the accurate estimation of rare event or failure...
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04/22/2022
Robust and efficient primal-dual Newton-Krylov solvers for viscous-plastic sea-ice models
We present a Newton-Krylov solver for a viscous-plastic sea-ice model. T...
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02/22/2022
A gradient-free subspace-adjusting ensemble sampler for infinite-dimensional Bayesian inverse problems
Sampling of sharp posteriors in high dimensions is a challenging problem...
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12/20/2021
Bayesian neural network priors for edge-preserving inversion
We consider Bayesian inverse problems wherein the unknown state is assum...
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11/29/2021
Estimating earthquake-induced tsunami inundation probabilities without sampling
Given a distribution of earthquake-induced seafloor elevations, we prese...
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07/02/2021
Robust multigrid techniques for augmented Lagrangian preconditioning of incompressible Stokes equations with extreme viscosity variations
We present augmented Lagrangian Schur complement preconditioners and rob...
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10/01/2020
Single-stage gradient-based stellarator coil design: Optimization for near-axis quasi-symmetry
We present a new coil design paradigm for magnetic confinement in stella...
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07/28/2020
Extreme event probability estimation using PDE-constrained optimization and large deviation theory, with application to tsunamis
We propose and compare methods for the estimation of extreme event proba...
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06/21/2020
Optimal design of large-scale Bayesian linear inverse problems under reducible model uncertainty: good to know what you don't know
We consider optimal design of infinite-dimensional Bayesian linear inver...
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03/24/2020
Advanced Newton Methods for Geodynamical Models of Stokes Flow with Viscoplastic Rheologies
Strain localization and resulting plasticity and failure play an importa...
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03/23/2020
Hierarchical Matrix Approximations of Hessians Arising in Inverse Problems Governed by PDEs
Hessian operators arising in inverse problems governed by partial differ...
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03/20/2020
Bayesian approach to inverse scattering with topological priors
We propose a Bayesian inference framework to estimate uncertainties in i...
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12/18/2019
Optimal experimental design under irreducible uncertainty for inverse problems governed by PDEs
We present a method for computing A-optimal sensor placements for infini...
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09/23/2019
Scalable Simulation of Realistic Volume Fraction Red Blood Cell Flows through Vascular Networks
High-resolution blood flow simulations have potential for developing bet...
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08/16/2018
A comparative study of structural similarity and regularization for joint inverse problems governed by PDEs
Joint inversion refers to the simultaneous inference of multiple paramet...
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04/16/2018