Noemi Petra

Noemi Petra

University of California, Merced

H-index: 16

North America-United States

About Noemi Petra

Noemi Petra, With an exceptional h-index of 16 and a recent h-index of 15 (since 2020), a distinguished researcher at University of California, Merced, specializes in the field of Inverse problems, PDE-constrained optimization, Uncertainty Quantification, Optimal Experimental Design.

His recent articles reflect a diverse array of research interests and contributions to the field:

Democratizing Uncertainty Quantification

Point spread function approximation of high rank Hessians with locally supported non-negative integral kernels

On the implementation of a quasi-Newton interior-point method for PDE-constrained optimization using finite element discretizations

Hierarchical off-diagonal low-rank approximation of Hessians in inverse problems, with application to ice sheet model initialization

hIPPYlib-MUQ: A Bayesian inference software framework for integration of data with complex predictive models under uncertainty

On global normal linear approximations for nonlinear Bayesian inverse problems

Further analysis of multilevel Stein variational gradient descent with an application to the Bayesian inference of glacier ice models

Optimal design of large-scale nonlinear Bayesian inverse problems under model uncertainty

Noemi Petra Information

University

Position

Associate Professor

Citations(all)

1584

Citations(since 2020)

1090

Cited By

966

hIndex(all)

16

hIndex(since 2020)

15

i10Index(all)

20

i10Index(since 2020)

18

Email

University Profile Page

University of California, Merced

Google Scholar

View Google Scholar Profile

Noemi Petra Skills & Research Interests

Inverse problems

PDE-constrained optimization

Uncertainty Quantification

Optimal Experimental Design

Top articles of Noemi Petra

Title

Journal

Author(s)

Publication Date

Democratizing Uncertainty Quantification

arXiv preprint arXiv:2402.13768

Linus Seelinger

Anne Reinarz

Mikkel B Lykkegaard

Amal Mohammed A Alghamdi

David Aristoff

...

2024/2/21

Point spread function approximation of high rank Hessians with locally supported non-negative integral kernels

arXiv preprint arXiv:2307.03349

Nick Alger

Tucker Hartland

Noemi Petra

Omar Ghattas

2023/7/7

On the implementation of a quasi-Newton interior-point method for PDE-constrained optimization using finite element discretizations

Optimization Methods and Software

Cosmin G Petra

Miguel Salazar De Troya

Noemi Petra

Youngsoo Choi

Geoffrey M Oxberry

...

2023/1/2

Hierarchical off-diagonal low-rank approximation of Hessians in inverse problems, with application to ice sheet model initialization

Inverse Problems

Tucker Hartland

Georg Stadler

Mauro Perego

Kim Liegeois

Noémi Petra

2023/6/26

hIPPYlib-MUQ: A Bayesian inference software framework for integration of data with complex predictive models under uncertainty

ACM Transactions on Mathematical Software

Ki-Tae Kim

Umberto Villa

Matthew Parno

Youssef Marzouk

Omar Ghattas

...

2023/6/15

On global normal linear approximations for nonlinear Bayesian inverse problems

Inverse Problems

Ruanui Nicholson

Noémi Petra

Umberto Villa

Jari P Kaipio

2023/3/17

Further analysis of multilevel Stein variational gradient descent with an application to the Bayesian inference of glacier ice models

arXiv preprint arXiv:2212.03366

Terrence Alsup

Tucker Hartland

Benjamin Peherstorfer

Noemi Petra

2022/12/6

Optimal design of large-scale nonlinear Bayesian inverse problems under model uncertainty

arXiv preprint arXiv:2211.03952

Alen Alexanderian

Ruanui Nicholson

Noemi Petra

2023

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 (TOMS)

Umberto Villa

Noemi Petra

Omar Ghattas

2021/4/1

Inversion for the Basal Sliding Coefficient Field under Uncertainty for the Humboldt Glacier.

AGU Fall Meeting Abstracts

Tucker Hartland

Mauro Perego

Georg Stadler

Noemi Petra

2021/12

Bound Constrained Partial DifferentialEquation Inverse Problem Solution by theSemi-Smooth Newton Method

Tucker Hartland

Cosmin G Petra

Noemi Petra

Jingyi Wang

2021/2/9

Joint parameter and model dimension reduction for Bayesian ice sheet inverse problems governed by the nonlinear Stokes equations

AGU Fall Meeting Abstracts

Noemi Petra

Ki-Tae Kim

Tiangang Cui

Benjamin Peherstorfer

2021/12

Second order adjoints in optimization

Noémi Petra

Ekkehard W Sachs

2021

Inversion of the Humboldt Glacier Basal Friction Coefficient Field in an Uncertain Ice Sheet Model.

Tucker Hartland

Mauro Perego

Noemi Petra

2021/8/1

Optimal design of large-scale Bayesian linear inverse problems under reducible model uncertainty: Good to know what you don't know

SIAM/ASA Journal on Uncertainty Quantification

Alen Alexanderian

Noemi Petra

Georg Stadler

Isaac Sunseri

2021

Hierarchical off-diagonal Hessian approximation for Bayesian inverse problems with application to the flow of the Greenland ice sheet.

Tucker Hartland

Georg Stadler

Mauro Perego

Kim Anne J Liegeois

Noemi Petra

2021/6/1

Inferring the basal sliding coefficient field for the Stokes ice sheet model under rheological uncertainty

The Cryosphere

Olalekan Babaniyi

Ruanui Nicholson

Umberto Villa

Noémi Petra

2021/4/9

On the derivation of quasi-Newton formulas for optimization in function spaces

Numerical Functional Analysis and Optimization

Radoslav G Vuchkov

Cosmin G Petra

Noémi Petra

2020/7/11

Linearized Bayesian inference for Young’s modulus parameter field in an elastic model of slender structures

Proceedings of the Royal Society A

Soheil Fatehiboroujeni

Noemi Petra

Sachin Goyal

2020/6/24

Statistical treatment of inverse problems constrained by differential equations-based models with stochastic terms

SIAM/ASA Journal on Uncertainty Quantification

Emil M Constantinescu

Noémi Petra

Julie Bessac

Cosmin G Petra

2020

See List of Professors in Noemi Petra University(University of California, Merced)

Co-Authors

H-index: 83
Michael Gurnis

Michael Gurnis

California Institute of Technology

H-index: 57
Jari Kaipio

Jari Kaipio

University of Auckland

H-index: 37
Georg Stadler

Georg Stadler

New York University

H-index: 24
Zheng Zhang

Zheng Zhang

University of California, Santa Barbara

H-index: 21
Alen Alexanderian

Alen Alexanderian

North Carolina State University

H-index: 7
Soheil Fatehiboroujeni

Soheil Fatehiboroujeni

Cornell University

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