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Felix Oghenekohwo and Felix J. Herrmann, Assessing the need for repeatability in acquisition of time-lapse data, in CSEG Annual Conference Proceedings, 2013.
Felix Oghenekohwo and Felix J. Herrmann, Improved time-lapse data repeatability with randomized sampling and distributed compressive sensing, in EAGE Annual Conference Proceedings, 2017.
Felix Oghenekohwo, Rajiv Kumar, and Felix J. Herrmann, Randomized sampling without repetition in time-lapse surveys, in SEG Technical Program Expanded Abstracts, 2014, pp. 4848-4852.
Felix Oghenekohwo, Rajiv Kumar, Ernie Esser, and Felix J. Herrmann, Using common information in compressive time-lapse full-waveform inversion, in EAGE Annual Conference Proceedings, 2015.
Felix Oghenekohwo, Rajiv Kumar, Ernie Esser, and Felix J. Herrmann, Time-lapse FWI with distributed compressed sensing, in Inaugural Full-Waveform Inversion Workshop, 2015.
Felix Oghenekohwo, Ernie Esser, and Felix J. Herrmann, Time-lapse seismic without repetition: reaping the benefits from randomized sampling and joint recovery, in EAGE Annual Conference Proceedings, 2014.
Felix Oghenekohwo and Felix J. Herrmann, A new take on compressive time-lapse seismic acquisition, imaging and inversion, in PIMS Workshop on Advances in Seismic Imaging and Inversion, 2015.
Felix Oghenekohwo and Felix J. Herrmann, Compressive time-lapse seismic data processing using shared information, in CSEG Annual Conference Proceedings, 2015.
Ju-Won Oh, Dong-Joo Min, and Felix J. Herrmann, Re-establishment of gradient in frequency-domain elastic waveform inversion, in CSEG Annual Conference Proceedings, 2012.
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.
Rafael Orozco, Abhinav Prakash Gahlot, and Felix J. Herrmann, BEACON: Bayesian Experimental design Acceleration with Conditional Normalizing flows - a case study in optimal monitor well placement for CO2 sequestration, in International Meeting for Applied Geoscience and Energy, 2024.
Rafael Orozco, Ziyi Yin, Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann, Neural wave-based imaging with amortized uncertainty quantification, in Inverse Problems: Modelling and Simulation, 2024.
Rafael Orozco, Abhinav Prakash Gahlot, Peng Chen, Mathias Louboutin, and Felix J. Herrmann, Normalizing Flows for Bayesian Experimental Design in Imaging Applications, in EAGE Annual Conference Proceedings, 2024.
Rafael Orozco, Huseyin Tuna Erdinc, Mathias Louboutin, and Felix J. Herrmann, Industry-Scale Uncertainty-Aware Full Waveform Inference with Generative Models, in SIAM Conference on Computational Science and Engineering (CSE25), 2025.
Rafael Orozco, Ali Siahkoohi, Gabrio Rizzuti, Tristan van Leeuwen, and Felix J. Herrmann, Adjoint operators enable fast and amortized machine learning based Bayesian uncertainty quantification, in SPIE Medical Imaging Conference, 2023.
Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, Generative Seismic Kriging with Normalizing Flows, in International Meeting for Applied Geoscience and Energy, 2023.
Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, Amortized Bayesian Full Waveform Inversion and Experimental Design with Normalizing Flows, in International Meeting for Applied Geoscience and Energy, 2023.
Rafael Orozco, Mathias Louboutin, Ali Siahkoohi, Gabrio Rizzuti, Tristan van Leeuwen, and Felix J. Herrmann, Amortized normalizing flows for transcranial ultrasound with uncertainty quantification, in Medical Imaging with Deep Learning, 2023.
Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, Fast neural FWI with amortized uncertainty quantification, in International Meeting for Applied Geoscience and Energy, 2023.
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.
Rafael Orozco, Abhinav Prakash Gahlot, Peng Chen, Mathias Louboutin, and Felix J. Herrmann, Normalizing Flows for Bayesian Experimental Design in Imaging Applications, in SIAM Conference on Uncertainty Quantification, 2024.
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.
P
Bas Peters and Felix J. Herrmann, Wavefield-reconstruction inversion, in Conference on Applied Inverse Problems, 2015.

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