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2023
Yijun Zhang, Ziyi Yin, Oscar Lopez, Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann, “3D seismic survey design by maximizing the spectral gap”, in International Meeting for Applied Geoscience and Energy, 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, 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.
Mathias Louboutin, Ziyi Yin, Rafael Orozco, Thomas J. Grady II, Ali Siahkoohi, Gabrio Rizzuti, Philipp A. Witte, Olav Møyner, Gerard J. Gorman, and Felix J. Herrmann, “Learned multiphysics inversion with differentiable programming and machine learning”, The Leading Edge, vol. 42, pp. 452-516, 2023.
Mathias Louboutin, Rafael Orozco, Ali Siahkoohi, and Felix J. Herrmann, “Learned non-linear simultenous source and corresponding supershot for seismic imaging.”, in International Meeting for Applied Geoscience and Energy, 2023.
Yijun Zhang, Ziyi Yin, Oscar Lopez, Ali Siahkoohi, Mathias Louboutin, Rajiv Kumar, and Felix J. Herrmann, “Optimized time-lapse acquisition design via spectral gap ratio minimization”, Geophysics, vol. 88, pp. A19-A23, 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.
Ali Siahkoohi, Gabrio Rizzuti, Rafael Orozco, and Felix J. Herrmann, “Reliable amortized variational inference with physics-based latent distribution correction”, Geophysics, vol. 88, 2023.
Ziyi Yin, Rafael Orozco, Mathias Louboutin, Ali Siahkoohi, and Felix J. Herrmann, “Uncertainty-aware time-lapse monitoring of geological carbon storage with learned surrogates”, in Engineering Mechanics Institute Conference, 2023.
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”, Journal of Open Source Software, vol. 9, 2024.
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, 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, Ziyi Yin, Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann, “Neural wave-based imaging with amortized uncertainty quantification”, ICL Seminar. 2024.
2025
Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann, “ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems”, Inverse Problems, vol. 41, 2025.
Huseyin Tuna Erdinc, Souza, T., and Felix J. Herrmann, “SAGE — Subsurface foundational model with AI-driven Geostatistical Extraction”, in EAGE Workshop, 2025.
Huseyin Tuna Erdinc, Bhar, I., Souza, T., Rafael Orozco, and Felix J. Herrmann, “SAGE - Subsurface modeling with AI-driven Geostatistical Extraction and evaluation on North Sea Data”, in ML4SEISMIC Partners Meeting, 2025.
I. Bhar, Huseyin Tuna Erdinc, Souza, T., Rafael Orozco, and Felix J. Herrmann, “Seismic Dataset Curation from UK National Data Repository to Validate SAGE and WISE”, in ML4SEISMIC Partners Meeting, 2025.
Huseyin Tuna Erdinc, Souza, T., Zeng, S., Rafael Orozco, and Felix J. Herrmann, “Towards foundation models for subsurface priors and posteriors”, in Workshop on Scientific Machine Learning 2025, Austin, TX, 2025.

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