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Ali Siahkoohi, Gabrio Rizzuti, and Felix J. Herrmann, A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification, in EAGE Annual Conference Proceedings, 2020.
Ali Siahkoohi, Rafael Orozco, Gabrio Rizzuti, and Felix J. Herrmann, 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).
Ali Siahkoohi, Gabrio Rizzuti, and Felix J. Herrmann, Uncertainty quantification in imaging and automatic horizon tracking—a Bayesian deep-prior based approach, in SEG Technical Program Expanded Abstracts, 2020, pp. 1636-1640.
Ali Siahkoohi, Thomas J. Grady II, Abhinav Prakash Gahlot, Huseyin Tuna Erdinc, and Felix J. Herrmann, 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).
Ali Siahkoohi, Gabrio Rizzuti, and Felix J. Herrmann, Weak deep priors for seismic imaging, in SEG Technical Program Expanded Abstracts, 2020, pp. 2998-3002.
Ali Siahkoohi, Chinen, M., Denton, T., W. Kleijn, B., and Skoglund, J., Ultra-Low-Bitrate Speech Coding with Pretrained Transformers, in Proceedings of INTERSPEECH, 2022.
Ali Siahkoohi, Gabrio Rizzuti, Rafael Orozco, and Felix J. Herrmann, Reliable amortized variational inference with conditional normalizing flows via physics-based latent distribution correction, in IMAGE Workshop on Subsurface Uncertainty Description and Estimation - Moving Away from Single Prediction with Distribution Learning, 2022.
Ali Siahkoohi, Rajiv Kumar, and Felix J. Herrmann, Seismic data reconstruction with Generative Adversarial Networks, in EAGE Annual Conference Proceedings, 2018.
Ali Siahkoohi, Philipp A. Witte, Mathias Louboutin, Felix J. Herrmann, and Gabrio Rizzuti, Seismic Imaging with Uncertainty Quantification: Sampling from the Posterior with Generative Networks, in SIAM Conference on Imaging Science, 2020.
Ali Siahkoohi, Gabrio Rizzuti, Mathias Louboutin, and Felix J. Herrmann, Unsupervised data-guided uncertainty analysis in imaging and horizon tracking, in SIAM Texas-Louisiana, 2020.
Ali Siahkoohi, Gabrio Rizzuti, Mathias Louboutin, Philipp A. Witte, and Felix J. Herrmann, Preconditioned training of normalizing flows for variational inference in inverse problems, in 3rd Symposium on Advances in Approximate Bayesian Inference, 2021.
Ali Siahkoohi, Gabrio Rizzuti, Mathias Louboutin, Philipp A. Witte, and Felix J. Herrmann, Deep Bayesian Inference for Task-based Seismic Imaging, in KAUST, 2021.
Ali Siahkoohi and Felix J. Herrmann, Learning by example: fast reliability-aware seismic imaging with normalizing flows, in SEG Technical Program Expanded Abstracts, 2021, pp. 1580-1585.
Ali Siahkoohi, Rafael Orozco, Gabrio Rizzuti, Philipp A. Witte, Mathias Louboutin, and Felix J. Herrmann, Fast and reliability-aware seismic imaging with conditional normalizing flows, in Intelligent illumination of the Earth, 2021.
Ali Siahkoohi, Rajiv Kumar, and Felix J. Herrmann, Deep-learning based ocean bottom seismic wavefield recovery, in SEG Technical Program Expanded Abstracts, 2019, pp. 2232-2237.
Ali Siahkoohi, Dirk J. Verschuur, and Felix J. Herrmann, Surface-related multiple elimination with deep learning, in SEG Technical Program Expanded Abstracts, 2019, pp. 4629-4634.
Brendan R. Smithyman, Bas Peters, and Felix J. Herrmann, Constrained waveform inversion of colocated VSP and surface seismic data, in EAGE Annual Conference Proceedings, 2015.

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