Biblio
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Author Title [ Type
] Year Filters: Keyword is seismic imaging and Author is Ali Siahkoohi [Clear All Filters]
, “Capturing velocity-model uncertainty and two-phase flow with Fourier Neural Operators”, in EAGE Annual Conference Proceedings, 2022, p. AI in Geoscience and Geophysics: Current Trends and Future Prospects (Dedicated Session).
, “Deep Bayesian Inference for Task-based Seismic Imaging”, in KAUST, 2021.
, “A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification”, in EAGE Annual Conference Proceedings, 2020.
, “Fast and reliability-aware seismic imaging with conditional normalizing flows”, in Intelligent illumination of the Earth, 2021.
, “Learned wave-based imaging - variational inference at scale”, in Delft, 2021.
, “Learning by example: fast reliability-aware seismic imaging with normalizing flows”, in SEG Technical Program Expanded Abstracts, 2021, pp. 1580-1585.
, “Wave-equation based inversion with amortized variational Bayesian inference”, in EAGE Annual Conference Proceedings, 2022, p. Session 2: Velocity model building and imaging (different domains).
, “Weak deep priors for seismic imaging”, in SEG Technical Program Expanded Abstracts, 2020, pp. 2998-3002.
, “Deep Bayesian inference for seismic imaging with tasks”, Geophysics, vol. 87, pp. 281-302, 2022.
, “Reliable amortized variational inference with physics-based latent distribution correction”, Geophysics, vol. 88, 2023.
, “A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification”, GT SEG Student Chapter. 2020.
, “Low-cost uncertainty quantification for large-scale inverse problems”, ML4SEISMIC Partners Meeting. 2022.
, “Multifidelity conditional normalizing flows for physics-guided Bayesian inference”, ML4SEISMIC Partners Meeting. 2021.