Noemi Petra
Orcid: 0000-0002-9491-0034
According to our database1,
Noemi Petra
authored at least 18 papers
between 2011 and 2024.
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Bibliography
2024
2023
hIPPYlib-MUQ: A Bayesian Inference Software Framework for Integration of Data with Complex Predictive Models under Uncertainty.
ACM Trans. Math. Softw., June, 2023
On the implementation of a quasi-Newton interior-point method for PDE-constrained optimization using finite element discretizations.
Optim. Methods Softw., January, 2023
Point spread function approximation of high rank Hessians with locally supported non-negative integral kernels.
CoRR, 2023
Hierarchical off-diagonal low-rank approximation of Hessians in inverse problems, with application to ice sheet model initializaiton.
CoRR, 2023
2022
Further analysis of multilevel Stein variational gradient descent with an application to the Bayesian inference of glacier ice models.
CoRR, 2022
Optimal design of large-scale nonlinear Bayesian inverse problems under model uncertainty.
CoRR, 2022
2021
hIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems Governed by PDEs: Part I: Deterministic Inversion and Linearized Bayesian Inference.
ACM Trans. Math. Softw., 2021
Optimal Design of Large-scale Bayesian Linear Inverse Problems Under Reducible Model Uncertainty: Good to Know What You Don't Know.
SIAM/ASA J. Uncertain. Quantification, 2021
2020
Statistical Treatment of Inverse Problems Constrained by Differential Equations-Based Models with Stochastic Terms.
SIAM/ASA J. Uncertain. Quantification, 2020
2018
J. Open Source Softw., 2018
2017
Mean-Variance Risk-Averse Optimal Control of Systems Governed by PDEs with Random Parameter Fields Using Quadratic Approximations.
SIAM/ASA J. Uncertain. Quantification, 2017
2016
A Fast and Scalable Method for A-Optimal Design of Experiments for Infinite-dimensional Bayesian Nonlinear Inverse Problems.
SIAM J. Sci. Comput., 2016
Scalable Algorithms for Bayesian Inference of Large-Scale Models from Large-Scale Data.
Proceedings of the High Performance Computing for Computational Science - VECPAR 2016, 2016
2015
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.
J. Comput. Phys., 2015
2014
A Computational Framework for Infinite-Dimensional Bayesian Inverse Problems, Part II: Stochastic Newton MCMC with Application to Ice Sheet Flow Inverse Problems.
SIAM J. Sci. Comput., 2014
A-Optimal Design of Experiments for Infinite-Dimensional Bayesian Linear Inverse Problems with Regularized ℓ<sub>0</sub>-Sparsification.
SIAM J. Sci. Comput., 2014
2011
SIAM J. Appl. Math., 2011