| Learned imaging with constraints and uncertainty quantification FJ Herrmann, A Siahkoohi, G Rizzuti arXiv preprint arXiv:1909.06473, 2019 | 30 | 2019 |
| 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 | 28 | 2021 |
| 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 | 22 | 2020 |
| 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 | 20 | 2020 |
| Multigrid-based ‘shifted-Laplacian’preconditioning for the time-harmonic elastic wave equation G Rizzuti, WA Mulder Journal of Computational Physics 317, 47-65, 2016 | 20 | 2016 |
| Reliable amortized variational inference with physics-based latent distribution correction A Siahkoohi, G Rizzuti, R Orozco, FJ Herrmann Geophysics 88 (3), R297-R322, 2023 | 17 | 2023 |
| Deep Bayesian inference for seismic imaging with tasks A Siahkoohi, G Rizzuti, FJ Herrmann Geophysics 87 (5), S281-S302, 2022 | 17 | 2022 |
| 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 | 17 | 2020 |
| Learned iterative solvers for the Helmholtz equation G Rizzuti, A Siahkoohi, FJ Herrmann 81st EAGE Conference and Exhibition 2019 2019 (1), 1-5, 2019 | 17 | 2019 |
| 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 | 16 | 2021 |
| 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 | 16 | 2019 |
| Faster uncertainty quantification for inverse problems with conditional normalizing flows A Siahkoohi, G Rizzuti, PA Witte, FJ Herrmann arXiv preprint arXiv:2007.07985, 2020 | 15 | 2020 |
| 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 | 14 | 2017 |
| 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 | 10 | 2023 |
| Weak deep priors for seismic imaging A Siahkoohi, G Rizzuti, FJ Herrmann SEG Technical Program Expanded Abstracts 2020, 2998-3002, 2020 | 9 | 2020 |
| 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 | 8 | 2021 |
| 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 | 7 | 2023 |
| 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 | 6 | 2023 |
| 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 | 6 | 2022 |
| Accelerating innovation with software abstractions for scalable computational geophysics M Louboutin, P Witte, A Siahkoohi, G Rizzuti, Z Yin, R Orozco, ... Second International Meeting for Applied Geoscience & Energy, 1482-1486, 2022 | 5 | 2022 |
Felix J. HerrmannProfessor Schools of Earth and Atmospheric Sciences, Computational Science and EngineeringVerified email at gatech.edu
