Noemi Petra

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 16

Top Topics

Inverse Problems

Top Venues

SIAM J. Sci. Comput.

SIAM/ASA J. Uncertain. Quantification

ACM Trans. Math. Softw.

Publications

Terrence Alsup, Tucker Hartland, Benjamin Peherstorfer, Noemi Petra
Further analysis of multilevel Stein variational gradient descent with an application to the Bayesian inference of glacier ice models. Adv. Comput. Math. 50 (4) (2024)
Linus Seelinger, Anne Reinarz, Mikkel Bue Lykkegaard, Amal Mohammed A. Alghamdi, David Aristoff, Wolfgang Bangerth, Jean Bénézech, Matteo Diez, Kurt Frey, John D. Jakeman, Jakob Sauer Jørgensen, Ki-Tae Kim, Massimiliano Martinelli, Matthew D. Parno, Riccardo Pellegrini, Noemi Petra, Nicolai André Brogaard Riis, Katherine Rosenfeld, Andrea Serani, Lorenzo Tamellini, Umberto Villa, Tim J. Dodwell, Robert Scheichl
Democratizing Uncertainty Quantification. CoRR (2024)
Nick Alger, Tucker Hartland, Noemi Petra, Omar Ghattas
Point Spread Function Approximation of High-Rank Hessians with Locally Supported Nonnegative Integral Kernels. SIAM J. Sci. Comput. 46 (3) (2024)
Ki-Tae Kim, Umberto Villa, Matthew D. Parno, Youssef M. Marzouk, Omar Ghattas, Noemi Petra
hIPPYlib-MUQ: A Bayesian Inference Software Framework for Integration of Data with Complex Predictive Models under Uncertainty. ACM Trans. Math. Softw. 49 (2) (2023)
Tucker Hartland, Georg Stadler, Mauro Perego, Kim Liegeois, Noemi Petra
Hierarchical off-diagonal low-rank approximation of Hessians in inverse problems, with application to ice sheet model initializaiton. CoRR (2023)
Cosmin G. Petra, Miguel A. Salazar de Troya, Noemi Petra, Youngsoo Choi, Geoffrey M. Oxberry, Daniel A. Tortorelli
On the implementation of a quasi-Newton interior-point method for PDE-constrained optimization using finite element discretizations. Optim. Methods Softw. 38 (1) (2023)
Nick Alger, Tucker Hartland, Noemi Petra, Omar Ghattas
Point spread function approximation of high rank Hessians with locally supported non-negative integral kernels. CoRR (2023)
Alen Alexanderian, Ruanui Nicholson, Noemi Petra
Optimal design of large-scale nonlinear Bayesian inverse problems under model uncertainty. CoRR (2022)
Umberto Villa, Noemi Petra, Omar Ghattas
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. 47 (2) (2021)
Ki-Tae Kim, Umberto Villa, Matthew Parno, Youssef Marzouk, Omar Ghattas, Noemi Petra
hIPPYlib-MUQ: A Bayesian Inference Software Framework for Integration of Data with Complex Predictive Models under Uncertainty. CoRR (2021)
Alen Alexanderian, Noemi Petra, Georg Stadler, Isaac Sunseri
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 9 (1) (2021)
Umberto Villa, Noemi Petra, Omar Ghattas
hIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems Governed by PDEs; Part I: Deterministic Inversion and Linearized Bayesian Inference. CoRR (2019)
Umberto Villa, Noemi Petra, Omar Ghattas
hIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems. J. Open Source Softw. 3 (30) (2018)
Alen Alexanderian, Noemi Petra, Georg Stadler, Omar Ghattas
Mean-Variance Risk-Averse Optimal Control of Systems Governed by PDEs with Random Parameter Fields Using Quadratic Approximations. SIAM/ASA J. Uncertain. Quantification 5 (1) (2017)
Alen Alexanderian, Noemi Petra, Georg Stadler, Omar Ghattas
A Fast and Scalable Method for A-Optimal Design of Experiments for Infinite-dimensional Bayesian Nonlinear Inverse Problems. SIAM J. Sci. Comput. 38 (1) (2016)
Tobin Isaac, Noemi Petra, Georg Stadler, Omar Ghattas
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. 296 (2015)
Alen Alexanderian, Noemi Petra, Georg Stadler, Omar Ghattas
-Sparsification. SIAM J. Sci. Comput. 36 (5) (2014)
Noemi Petra, James Martin, Georg Stadler, Omar Ghattas
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. 36 (4) (2014)
Noemi Petra, John Zweck, Susan E. Minkoff, Anatoliy Kosterev, James H. Doty III
Modeling and Design Optimization of a Resonant Optothermoacoustic Trace Gas Sensor. SIAM J. Appl. Math. 71 (1) (2011)