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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, Haneet Wason, and Felix J. Herrmann, “Asymmetric sampling for time-lapse surveys”, SINBAD Fall consortium talks. SINBAD, 2016.
Felix Oghenekohwo, Haneet Wason, Ernie Esser, and Felix J. Herrmann, “Randomized sampling without repetition in time-lapse seismic surveys”, SINBAD Spring consortium talks. SINBAD, 2014.
Felix Oghenekohwo, Rajiv Kumar, Ernie Esser, and Felix J. Herrmann, “Use what`s in common: time-lapse FWI with distributed Compressive Sensing”, SINBAD Fall consortium talks. SINBAD, 2014.
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, Ernie Esser, and Felix J. Herrmann, “Estimating 4D differences in time-lapse using randomized sampling techniques”, SINBAD Fall consortium talks. SINBAD, 2013.
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, Rajiv Kumar, Haneet Wason, Ernie Esser, and Felix J. Herrmann, “Randomized subsampling in time-lapse surveys and recovery techniques”, SINBAD Fall consortium talks. SINBAD, 2014.
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, Philipp A. Witte, Mathias Louboutin, Ali Siahkoohi, Gabrio Rizzuti, Bas Peters, and Felix J. Herrmann, “InvertibleNetworks.jl: A Julia package for scalable normalizing flows”, Journal of Open Source Software, vol. 9, 2024.
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.
Rafael Orozco, Mathias Louboutin, Ali Siahkoohi, Gabrio Rizzuti, and Felix J. Herrmann, “Adjoint operators as summary functions in amortized Bayesian inference frameworks”, ML4SEISMIC Partners Meeting. 2022.
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, Mathias Louboutin, Peng Chen, and Felix J. Herrmann, “Uncertainty quantification so what? Leveraging probabilistic seismic inversion for experimental design”, ML4SEISMIC Partners Meeting. 2023.
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, Ali Siahkoohi, Gabrio Rizzuti, and Felix J. Herrmann, “Variational inference for artifact removal of adjoint solutions in photoacoustic problems”, ML4SEISMIC Partners Meeting. 2021.
Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “Normalizing flows for regularization of 3D seismic inverse problems”, ML4SEISMIC Partners Meeting. 2022.
Rafael Orozco, “GENERATIVE MODELS FOR UNCERTAINTY QUANTIFICATION OF MEDICAL AND SEISMIC IMAGING”, Georgia Institute of Technology, Atlanta, 2024.
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, Mathias Louboutin, and Felix J. Herrmann, “Memory Efficient Invertible Neural Networks for 3D Photoacoustic Imaging”, TR-CSE-2022-2, 2022.
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.

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