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Shashin Sharan, Rongrong Wang, and Felix J. Herrmann, “High resolution fast microseismic source collocation and source time function estimation”, in SEG Technical Program Expanded Abstracts, 2017, pp. 2778-2783.
Gang Tang, Reza Shahidi, Felix J. Herrmann, and Jianwei Ma, “Higher dimensional blue-noise sampling schemes for curvelet-based seismic data recovery”, in SEG Technical Program Expanded Abstracts, 2009, vol. 28, pp. 191-195.
Yijun Zhang, Shashin Sharan, and Felix J. Herrmann, “High-frequency wavefield recovery with weighted matrix factorizations”, in SEG Technical Program Expanded Abstracts, 2019, pp. 3959-3963.
Tristan van Leeuwen, Mark Schmidt, Michael P. Friedlander, and Felix J. Herrmann, “A hybrid stocahstic-deterministic method for waveform inversion”, in AMP, 2011.
Tristan van Leeuwen, Felix J. Herrmann, Mark Schmidt, and Michael P. Friedlander, “A hybrid stochastic-deterministic optimization method for waveform inversion”, in EAGE Annual Conference Proceedings, 2011.
Philipp A. Witte, Mathias Louboutin, Ali Siahkoohi, Gabrio Rizzuti, Bas Peters, and Felix J. Herrmann, “InvertibleNetworks.jl - Memory efficient deep learning in Julia”, in JuliaCon, 2021.
Ziyi Yin, Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann, “Learned coupled inversion for carbon sequestration monitoring and forecasting with Fourier neural operators”, in International Meeting for Applied Geoscience and Energy Expanded Abstracts, 2022.
Felix J. Herrmann, Ali Siahkoohi, and Gabrio Rizzuti, “Learned imaging with constraints and uncertainty quantification”, in Neural Information Processing Systems (NeurIPS), 2019.
Gabrio Rizzuti, Ali Siahkoohi, and Felix J. Herrmann, “Learned iterative solvers for the Helmholtz equation”, in EAGE Annual Conference Proceedings, 2019.
Mathias Louboutin, Rafael Orozco, Ali Siahkoohi, and Felix J. Herrmann, “Learned non-linear simultenous source and corresponding supershot for seismic imaging.”, in International Meeting for Applied Geoscience and Energy, 2023.
Felix J. Herrmann, Ali Siahkoohi, Rafael Orozco, Gabrio Rizzuti, Philipp A. Witte, and Mathias Louboutin, “Learned wave-based imaging - variational inference at scale”, in Delft, 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.
Peyman P. Moghaddam, Felix J. Herrmann, and Christiaan C. Stolk, “Migration amplitude recovery using curvelets”, in CSEG Annual Conference Proceedings, 2007.
Felix J. Herrmann, Mathias Louboutin, and Ali Siahkoohi, “ML@scale using randomized linear algebra”, in Microsoft, 2021.
Challa S. Sastry, “Norm-one recovery from irregular sampled data”, in SINBAD 2007, 2007.
Ewout van den Berg, Mark Schmidt, Michael P. Friedlander, and K. Murphy, “Optimizing costly functions with simple constraints: a limited-memory projected Quasi-Newton algorithm”, in SLIM, 2009, vol. 12.
Gabrio Rizzuti, Ali Siahkoohi, Philipp A. Witte, and Felix J. Herrmann, “Parameterizing uncertainty by deep invertible networks, an application to reservoir characterization”, in SEG Technical Program Expanded Abstracts, 2020, pp. 1541-1545.
Philipp A. Witte, Christiaan C. Stolk, and Felix J. Herrmann, “Phase velocity error minimizing scheme for the anisotropic pure P-wave equation”, in SEG Technical Program Expanded Abstracts, 2016, pp. 452-457.
Rafael Orozco, Ali Siahkoohi, Gabrio Rizzuti, Tristan van Leeuwen, and Felix J. Herrmann, “Photoacoustic Imaging with Conditional Priors from Normalizing Flows”, in Neural Information Processing Systems (NeurIPS), 2021.
Felix J. Herrmann, Gerard J. Gorman, Jan Hückelheim, Keegan Lensink, Paul H. J. Kelly, Navjot Kukreja, Henryk Modzelewski, Michael Lange, Mathias Louboutin, Fabio Luporini, Ali Siahkoohi, and Philipp A. Witte, “The power of abstraction in Computational Exploration Seismology”, in Smoky Mountains Computational Sciences and Engineering Conference, 2018.
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.
Deli Wang, Rayan Saab, Ozgur Yilmaz, and Felix J. Herrmann, “Recent results in curvelet-based primary-multiple separation”, in SINBAD 2008, 2008.
Deli Wang, Rayan Saab, Ozgur Yilmaz, and Felix J. Herrmann, “Recent results in curvelet-based primary-multiple separation: application to real data”, in SEG Technical Program Expanded Abstracts, 2007, vol. 26, pp. 2500-2504.
Challa S. Sastry, Gilles Hennenfent, and Felix J. Herrmann, “Recovery from unstructured data”, in SINBAD 2006, 2006.
Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann, “Refining Amortized Posterior Approximations using Gradient-Based Summary Statistics”, in 5th Symposium on Advances in Approximate Bayesian Inference, 2023.

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