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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, 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, 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, Zeng, S., and Felix J. Herrmann, “Amortized Full-Waveform Inference w/ Learned Summary Statistics”, in Reduced Order and Surrogate Modeling for Digital Twins, IMSI, Chicago, 2025.
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.
Rafael Orozco, Huseyin Tuna Erdinc, Souza, T., Yunlin Zeng, Ziyi Yin, and Felix J. Herrmann, “Machine-learning enabled velocity-model building with uncertainty quantification”, ML4SEISMIC Partners Meeting. 2024.
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, Mathias Louboutin, and Felix J. Herrmann, “Fast neural FWI with amortized uncertainty quantification”, in International Meeting for Applied Geoscience and Energy, 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, 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, “GENERATIVE MODELS FOR UNCERTAINTY QUANTIFICATION OF MEDICAL AND SEISMIC IMAGING”, Georgia Institute of Technology, Atlanta, 2024.
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”, Inverse Problems, vol. 41, 2025.
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.
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Sebastien Pacteau, “Kronecker product optimization in SPOT”, SINBAD Fall consortium talks. SINBAD, 2010.

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