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Ali Siahkoohi
Ali Siahkoohi
Simons Postdoctoral Fellow, Rice University
Verified email at rice.edu - Homepage
Title
Cited by
Cited by
Year
The importance of transfer learning in seismic modeling and imaging
A Siahkoohi, M Louboutin, FJ Herrmann
Geophysics 84 (6), A47-A52, 2019
822019
Seismic data reconstruction with generative adversarial networks
A Siahkoohi, R Kumar, F Herrmann
80th EAGE conference and exhibition 2018 2018 (1), 1-5, 2018
752018
Self-consuming generative models go MAD
S Alemohammad, J Casco-Rodriguez, L Luzi, AI Humayun, H Babaei, ...
International Conference on Learning Representations (ICLR), 2024
642024
Surface-related multiple elimination with deep learning
A Siahkoohi, DJ Verschuur, FJ Herrmann
SEG International Exposition and Annual Meeting, 2019
48*2019
Preconditioned training of normalizing flows for variational inference in inverse problems
A Siahkoohi, G Rizzuti, M Louboutin, PA Witte, FJ Herrmann
3rd Symposium on Advances in Approximate Bayesian Inference, 2021
35*2021
Learned imaging with constraints and uncertainty quantification
FJ Herrmann, A Siahkoohi, G Rizzuti
NeurIPS 2019 Deep Inverse Workshop, 2019
30*2019
Reliable amortized variational inference with physics-based latent distribution correction
A Siahkoohi, G Rizzuti, R Orozco, FJ Herrmann
Geophysics 88 (3), R297-R322, 2023
232023
Deep Bayesian inference for seismic imaging with tasks
A Siahkoohi, G Rizzuti, FJ Herrmann
Geophysics 87 (5), S281-S302, 2022
23*2022
Parameterizing uncertainty by deep invertible networks: An application to reservoir characterization
G Rizzuti, A Siahkoohi, PA Witte, FJ Herrmann
SEG Technical Program Expanded Abstracts 2020, 1541-1545, 2020
23*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
22*2020
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
22*2020
Faster uncertainty quantification for inverse problems with conditional normalizing flows
A Siahkoohi, G Rizzuti, PA Witte, FJ Herrmann
arXiv preprint arXiv:2007.07985, 2020
19*2020
Deep-convolutional neural networks in prestack seismic: Two exploratory examples
A Siahkoohi, M Louboutin, R Kumar, FJ Herrmann
SEG Technical Program Expanded Abstracts 2018, 2196-2200, 2018
192018
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
Learning by example: fast reliability-aware seismic imaging with normalizing flows
A Siahkoohi, FJ Herrmann
First International Meeting for Applied Geoscience & Energy, 1580-1585, 2021
17*2021
InvertibleNetworks.jl: A Julia package for scalable normalizing flows
R Orozco, P Witte, M Louboutin, A Siahkoohi, G Rizzuti, B Peters, ...
arXiv preprint arXiv:2312.13480, 2023
15*2023
Learned coupled inversion for carbon sequestration monitoring and forecasting with Fourier neural operators
Z Yin, A Siahkoohi, M Louboutin, FJ Herrmann
Second International Meeting for Applied Geoscience & Energy, 467-472, 2022
15*2022
Deep-learning based ocean bottom seismic wavefield recovery
A Siahkoohi, R Kumar, FJ Herrmann
SEG International Exposition and Annual Meeting, 2019
15*2019
Neural network augmented wave-equation simulation
A Siahkoohi, M Louboutin, FJ Herrmann
arXiv preprint arXiv:1910.00925, 2019
142019
Boomerang: Local sampling on image manifolds using diffusion models
L Luzi, PM Mayer, J Casco-Rodriguez, A Siahkoohi, RG Baraniuk
Transactions on Machine Learning Research, 2024
132024
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