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Felix Oghenekohwo, Haneet Wason, Ernie Esser, and Felix J. Herrmann, “Low-cost time-lapse seismic with distributed compressive sensing–-Part 1: exploiting common information among the vintages”, Geophysics, vol. 82, pp. P1-P13, 2017.
Felix Oghenekohwo, “Economic time-lapse seismic acquisition and imaging–-Reaping the benefits of randomized sampling with distributed compressive sensing”, The University of British Columbia, Vancouver, 2017.
Felix Oghenekohwo and Felix J. Herrmann, “Comparative study of time-lapse FWI approaches”, SINBAD Fall consortium talks. SINBAD, 2015.
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, Rajiv Kumar, Haneet Wason, Ernie Esser, Ning Tu, and Felix J. Herrmann, “Recent developments in compressive sensing for time-lapse studies”, SINBAD Spring consortium talks. SINBAD, 2015.
Felix Oghenekohwo and Felix J. Herrmann, “Time-lapse seismics with randomized sampling”, UBC, TR-EOAS-2013-3, 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, 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, Rajiv Kumar, Ernie Esser, and Felix J. Herrmann, “Time-lapse FWI with distributed compressed sensing”, in Inaugural Full-Waveform Inversion Workshop, 2015.
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.
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.
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, 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, Mathias Louboutin, and Felix J. Herrmann, “Towards generative seismic kriging with normalizing flows”, ML4SEISMIC Partners Meeting. 2023.
Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “Memory Efficient Invertible Neural Networks for 3D Photoacoustic Imaging”, TR-CSE-2022-2, 2022.
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, 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, Mathias Louboutin, and Felix J. Herrmann, “Fast neural FWI with amortized uncertainty quantification”, 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, “Amortized Bayesian Full Waveform Inversion and Experimental Design with Normalizing Flows”, in International Meeting for Applied Geoscience and Energy, 2023.
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.
Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann, “ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems”. 2024.
Rafael Orozco, Philipp A. Witte, Mathias Louboutin, Ali Siahkoohi, Gabrio Rizzuti, Bas Peters, and Felix J. Herrmann, “InvertibleNetworks.jl: A Julia package for scalable normalizing flows”. 2023.
Rafael Orozco, Ziyi Yin, Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann, “Neural wave-based imaging with amortized uncertainty quantification”, ICL Seminar. 2024.
Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “Generative Seismic Kriging with Normalizing Flows”, in International Meeting for Applied Geoscience and Energy, 2023.

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