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Gabrio Rizzuti
Gabrio Rizzuti
Shearwater Geoservics
Verified email at shearwatergeo.com
Title
Cited by
Cited by
Year
Learned imaging with constraints and uncertainty quantification
FJ Herrmann, A Siahkoohi, G Rizzuti
arXiv preprint arXiv:1909.06473, 2019
302019
Preconditioned training of normalizing flows for variational inference in inverse problems
A Siahkoohi, G Rizzuti, M Louboutin, PA Witte, FJ Herrmann
arXiv preprint arXiv:2101.03709, 2021
292021
Parameterizing uncertainty by deep invertible networks: An application to reservoir characterization
G Rizzuti, A Siahkoohi, PA Witte, FJ Herrmann
SEG International Exposition and Annual Meeting, D031S057R006, 2020
222020
A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification
A Siahkoohi, G Rizzuti, F Herrmann
EAGE 2020 Annual Conference & Exhibition Online 2020 (1), 1-5, 2020
202020
Multigrid-based ‘shifted-Laplacian’preconditioning for the time-harmonic elastic wave equation
G Rizzuti, WA Mulder
Journal of Computational Physics 317, 47-65, 2016
202016
Learned iterative solvers for the Helmholtz equation
G Rizzuti, A Siahkoohi, FJ Herrmann
81st EAGE Conference and Exhibition 2019 2019 (1), 1-5, 2019
182019
Deep Bayesian inference for seismic imaging with tasks
A Siahkoohi, G Rizzuti, FJ Herrmann
Geophysics 87 (5), S281-S302, 2022
172022
Uncertainty quantification in imaging and automatic horizon tracking—a Bayesian deep-prior based approach
A Siahkoohi, G Rizzuti, FJ Herrmann
SEG Technical Program Expanded Abstracts 2020, 1636-1640, 2020
172020
Reliable amortized variational inference with physics-based latent distribution correction
A Siahkoohi, G Rizzuti, R Orozco, FJ Herrmann
Geophysics 88 (3), R297-R322, 2023
162023
A dual formulation for time-domain wavefield reconstruction inversion
G Rizzuti, M Louboutin, R Wang, E Daskalakis, F Herrmann
SEG International Exposition and Annual Meeting, D043S130R005, 2019
162019
A dual formulation of wavefield reconstruction inversion for large-scale seismic inversion
G Rizzuti, M Louboutin, R Wang, FJ Herrmann
Geophysics 86 (6), R879-R893, 2021
152021
Faster uncertainty quantification for inverse problems with conditional normalizing flows
A Siahkoohi, G Rizzuti, PA Witte, FJ Herrmann
arXiv preprint arXiv:2007.07985, 2020
152020
An iterative method for 2D inverse scattering problems by alternating reconstruction of medium properties and wavefields: theory and application to the inversion of elastic …
G Rizzuti, A Gisolf
Inverse Problems 33 (3), 035003, 2017
142017
Amortized Normalizing Flows for Transcranial Ultrasound with Uncertainty Quantification
R Orozco, M Louboutin, A Siahkoohi, G Rizzuti, T van Leeuwen, ...
arXiv preprint arXiv:2303.03478, 2023
92023
Photoacoustic imaging with conditional priors from normalizing flows
R Orozco, A Siahkoohi, G Rizzuti, T van Leeuwen, FJ Herrmann
NeurIPS 2021 Workshop on Deep Learning and Inverse Problems, 2021
82021
Weak deep priors for seismic imaging
A Siahkoohi, G Rizzuti, FJ Herrmann
SEG Technical Program Expanded Abstracts 2020, 2998-3002, 2020
82020
Adjoint operators enable fast and amortized machine learning based Bayesian uncertainty quantification
R Orozco, A Siahkoohi, G Rizzuti, T van Leeuwen, FJ Herrmann
Medical Imaging 2023: Image Processing 12464, 357-367, 2023
72023
Joint retrospective motion correction and reconstruction for brain MRI with a reference contrast
G Rizzuti, A Sbrizzi, T Van Leeuwen
IEEE Transactions on Computational Imaging 8, 490-504, 2022
72022
Learned multiphysics inversion with differentiable programming and machine learning
M Louboutin, Z Yin, R Orozco, TJ Grady, A Siahkoohi, G Rizzuti, PA Witte, ...
The Leading Edge 42 (7), 474-486, 2023
52023
Wave-equation-based inversion with amortized variational Bayesian inference
A Siahkoohi, R Orozco, G Rizzuti, FJ Herrmann
arXiv preprint arXiv:2203.15881, 2022
52022
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