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researcher

O. Ghattas

53 papers hereh-index 6212.6k citations247 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author10
  • last author43

Across the 53 of 53 papers where every author was matched, so the position is known.

fields
  • math.NA23
  • math.OC14
  • physics.comp-ph3
  • cs.DC2
  • cs.LG2
  • physics.geo-ph2
same name
  • O. Ghattas — 1 paper, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20132023
most citedScalable 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

171 citations · 898 across the 46 of their papers we have counts for

collaborators
Showing 2023Show all

3 papers · 1 filter

math.NA2023

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

Nick Alger, Tucker Hartland, Noemi Petra +1

We present an efficient matrix-free point spread function (PSF) method for approximating operators that have locally supported non-negative integral kernels. The method computes im…

physics.comp-ph2023★ 1 cited

Bayesian model calibration for diblock copolymer thin film self-assembly using power spectrum of microscopy data and machine learning surrogate

Lianghao Cao, Keyi Wu, J. Tinsley Oden +2

Identifying parameters of computational models from experimental data, or model calibration, is fundamental for assessing and improving the predictability and reliability of comput…

math.OC2023★ 9 cited

Efficient PDE-Constrained optimization under high-dimensional uncertainty using derivative-informed neural operators

Dingcheng Luo, Thomas O'Leary-Roseberry, Peng Chen +1

We propose a novel machine learning framework for solving optimization problems governed by large-scale partial differential equations (PDEs) with high-dimensional random parameter…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.