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Ali Siahkoohi, Mathias Louboutin, Rajiv Kumar, and Felix J. Herrmann, “Deep Convolutional Neural Networks in prestack seismic–-two exploratory examples”, in SEG Technical Program Expanded Abstracts, 2018, pp. 2196-2200.
Ali Siahkoohi, “Deep generative models for solving geophysical inverse problems”, Georgia Institute of Technology, Atlanta, 2022.
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, Gabrio Rizzuti, and Felix J. Herrmann, “A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification”, GT SEG Student Chapter. 2020.
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.
Felix J. Herrmann, “(De)-Focused wavefield reconstructions”, in SINBAD 2008, 2008.
Rongrong Wang and Felix J. Herrmann, “A denoising formulation of full-waveform inversion”, in SEG Technical Program Expanded Abstracts, 2017, pp. 1594-1598.
Rajiv Kumar, Nick Moldoveanu, and Felix J. Herrmann, “Denoising high-amplitude cross-flow noise using curvelet-based stable principle component pursuit”, in EAGE Annual Conference Proceedings, 2017.
Rongrong Wang and Felix J. Herrmann, “Denoising the wavefield inversion problem through source blending and penalty method”, SINBAD Fall consortium talks. SINBAD, 2014.
Tim T.Y. Lin, Haneet Wason, and Felix J. Herrmann, “Dense shot-sampling via time-jittered marine sources”, in SEG Workshop on Simultaneous Sources; Houston, 2013.
Huseyin Tuna Erdinc, Abhinav Prakash Gahlot, Ziyi Yin, Mathias Louboutin, and Felix J. Herrmann, “De-risking Carbon Capture and Sequestration with Explainable CO$_2$ Leakage Detection in Time-lapse Seismic Monitoring Images”, in AAAI 2022 Fall Symposium: The Role of AI in Responding to Climate Challenges, 2022.
Huseyin Tuna Erdinc, Abhinav Prakash Gahlot, Ziyi Yin, Mathias Louboutin, and Felix J. Herrmann, “De-risking GCS projects with explainable CO$_2$ leakage detection in time-lapse seismic images”, ML4SEISMIC Partners Meeting. 2022.
Ziyi Yin, Huseyin Tuna Erdinc, Abhinav Prakash Gahlot, Mathias Louboutin, and Felix J. Herrmann, “Derisking geological carbon storage from high-resolution time-lapse seismic to explainable leakage detection”, The Leading Edge, vol. 42, pp. 69-76, 2023.
Felix J. Herrmann, Huseyin Tuna Erdinc, Abhinav Prakash Gahlot, Ziyi Yin, and Mathias Louboutin, “Derisking geological storage with simulation-based seismic monitoring design and machine learning”, in Carbon, Capture, Utilization, and Storage, 2023.
Henryk Modzelewski, “Design and specifications for SLIM’s software framework”, in SINBAD 2008, 2008.
Henryk Modzelewski, “Design and specifications for SLIM’s software framework”, in SINBAD 2006, 2006.
Gang Tang, Reza Shahidi, and Jianwei Ma, “Design of two-dimensional randomized sampling schemes for curvelet-based sparsity-promoting seismic data recovery”, UBC Earth and Ocean Sciences Department, TR-EOAS-2009-3, 2009.
Tim T.Y. Lin and Felix J. Herrmann, “Designing simultaneous acquisitions with compressive sensing”, in EAGE Annual Conference Proceedings, 2009.
Oscar Lopez and Felix J. Herrmann, “Deterministic matrix completion: applications to seismic trace interpolation”, SINBAD Spring consortium talks. SINBAD, 2015.
Emmanouil Daskalakis, Rachel Kuske, and Felix J. Herrmann, “Developments in the direction of solving extremly large problems in Geophysics”, in SEG Technical Program Expanded Abstracts, 2017, pp. 4375-4378.
Navjot Kukreja, Mathias Louboutin, Felippe Vieira Zacarias, Fabio Luporini, Michael Lange, and Gerard Gorman, “Devito: automated fast finite difference computation”, in WOLFHPC 2016 Workshop (Super Computing), 2016.
Marcos de Aguiar, Gerard Gorman, Felix J. Herrmann, Navjot Kukreja, Michael Lange, Mathias Louboutin, and Felippe Vieira Zacarias, “DeVito: fast finite difference computation”, in Super Computing (SC16), 2016.
Navjot Kukreja, Michael Lange, Mathias Louboutin, Fabio Luporini, and Gerard Gorman, “Devito: symbolic math for automated fast finite difference computations”, in SIAM Conference on Computational Science and Engineering, 2017.
Michael Lange, Navjot Kukreja, Mathias Louboutin, Fabio Luporini, Felippe Vieira Zacarias, Vincenzo Pandolfo, Paulius Velesko, Paulius Kazakas, and Gerard Gorman, “Devito: Towards a generic finite difference DSL using symbolic python”, in 6th Workshop on Python for High-Performance and Scientific Computing, 2016, pp. 67-75.
Mathias Louboutin, Michael Lange, Fabio Luporini, Navjot Kukreja, Philipp A. Witte, Felix J. Herrmann, Paulius Velesko, and Gerard J. Gorman, “Devito (v3.1.0): an embedded domain-specific language for finite differences and geophysical exploration”, Geoscientific Model Development, 2019.

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