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Rajiv Kumar, Nick Moldoveanu, Keegan Lensink, and Felix J. Herrmann, “Full-azimuth seismic data processing w/ coil acquisition”, SINBAD Fall consortium talks. SINBAD, 2017.
Rongrong Wang, Ozgur Yilmaz, and Felix J. Herrmann, “Full waveform inversion with interferometric measurements”, UBC, TR-EOAS-2014-5, 2014.
Felix J. Herrmann, Aleksandr Y. Aravkin, Xiang Li, and Tristan van Leeuwen, “Full waveform inversion with compressive updates”, in SLRA, 2011.
Aleksandr Y. Aravkin, Felix J. Herrmann, Tristan van Leeuwen, James V. Burke, and Xiang Li, “Full waveform inversion with compressive updates”, in SIAM, 2011.
Felix J. Herrmann, “Frugal FWI”, SINBAD Fall consortium talks. SINBAD, 2013.
Felix J. Herrmann, “Frugal FWI”, SINBAD Spring consortium talks. SINBAD, 2013.
Felix J. Herrmann, Andrew J. Calvert, Ian Hanlon, Mostafa Javanmehri, Rajiv Kumar, Tristan van Leeuwen, Xiang Li, Brendan R. Smithyman, Eric Takam Takougang, and Haneet Wason, “Frugal full-waveform inversion: from theory to a practical algorithm”, The Leading Edge, vol. 32, pp. 1082-1092, 2013.
Felix J. Herrmann, “From seismic data to the composition of rocks: an interdisciplinary and multiscale approach to exploration seismology”, in Berkhout’s valedictory address: the conceptual approach of understanding, 2007.
Ju-Won Oh, Dong-Joo Min, and Felix J. Herrmann, “Frequency-domain elastic waveform inversion using weighting factors related to source-deconvolved residuals”, in EAGE Annual Conference Proceedings, 2012.
Rongrong Wang and Felix J. Herrmann, “Frequency down-extrapolation with TV norm minimization”, in SEG Technical Program Expanded Abstracts, 2016, pp. 1380-1384.
Felix J. Herrmann, “Focused recovery with the curvelet transform”, in SINBAD 2007, 2007.
Felix J. Herrmann, Michael P. Friedlander, and Ozgur Yilmaz, “Fighting the curse of dimensionality: compressive sensing in exploration seismology”, Signal Processing Magazine, IEEE, vol. 29, pp. 88-100, 2012.
Ali Siahkoohi, Gabrio Rizzuti, Philipp A. Witte, and Felix J. Herrmann, “Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows”, Georgia Institute of Technology, TR-CSE-2020-2, 2020.
Tristan van Leeuwen and Felix J. Herrmann, “Fast waveform inversion without source encoding”, Geophysical Prospecting, vol. 61, pp. 10-19, 2013.
Zhilong Fang, Curt Da Silva, and Felix J. Herrmann, “Fast uncertainty quantification for 2D full-waveform inversion with randomized source subsampling”, in EAGE Annual Conference Proceedings, 2014.
Shashin Sharan, Rongrong Wang, and Felix J. Herrmann, “Fast sparsity-promoting microseismic source estimation”, Geophysical Journal International, vol. 216, pp. 164-181, 2019.
Mengmeng Yang, Emmanouil Daskalakis, and Felix J. Herrmann, “Fast sparsity-promoting least-squares migration with multiples in time domain”, in SEG Technical Program Expanded Abstracts, 2017, pp. 4828-4832.
Felix J. Herrmann, “Fast sparsity-promoting imaging with message passing”, SINBAD Fall consortium talks. SINBAD, 2012.
Rafael Lago, Art Petrenko, Zhilong Fang, and Felix J. Herrmann, “Fast solution of time-harmonic wave-equation for full-waveform inversion”, in EAGE Annual Conference Proceedings, 2014.
Aleksandr Y. Aravkin, Xiang Li, and Felix J. Herrmann, “Fast seismic imaging for marine data”, in ICASSP, 2012.
Felix J. Herrmann and Ning Tu, “Fast RTM with multiples and source estimation”, in EAGE/SEG Forum - Turning noise into geological information: The next big step?, 2013.
Xiang Li, Aleksandr Y. Aravkin, Tristan van Leeuwen, and Felix J. Herrmann, “Fast randomized full-waveform inversion with compressive sensing”, Geophysics, vol. 77, pp. A13-A17, 2012.
Felix J. Herrmann, Ning Tu, and Ernie Esser, “Fast "online" migration with Compressive Sensing”, in EAGE Annual Conference Proceedings, 2015.
Felix J. Herrmann, “Fast “online” migration with Compressive Sensing”, SINBAD Spring consortium talks. SINBAD, 2015.
Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “Fast neural FWI with amortized uncertainty quantification”, in International Meeting for Applied Geoscience and Energy, 2023.

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