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07/07/2023
Point spread function approximation of high rank Hessians with locally supported non-negative integral kernels
We present an efficient matrix-free point spread function (PSF) method f...
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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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12/06/2022
Further analysis of multilevel Stein variational gradient descent with an application to the Bayesian inference of glacier ice models
Multilevel Stein variational gradient descent is a method for particle-b...
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11/08/2022
Optimal design of large-scale nonlinear Bayesian inverse problems under model uncertainty
We consider optimal experimental design (OED) for Bayesian nonlinear inv...
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12/01/2021
hIPPYlib-MUQ: A Bayesian Inference Software Framework for Integration of Data with Complex Predictive Models under Uncertainty
Bayesian inference provides a systematic framework for integration of da...
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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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09/09/2019
hIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems Governed by PDEs; Part I: Deterministic Inversion and Linearized Bayesian Inference
We present an extensible software framework, hIPPYlib, for solution of l...
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10/15/2018
Statistical Treatment of Inverse Problems Constrained by Differential Equations-Based Models with Stochastic Terms
This paper introduces a statistical treatment of inverse problems constr...
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01/11/2018