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Conference
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.
Abhinav Prakash Gahlot, Rafael Orozco, and Felix J. Herrmann, “Advancing Geological Carbon Storage Monitoring with 3D Digital Shadow Technology”, in EAGE Annual Conference Proceedings, 2025.
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.
Ali Siahkoohi, Gabrio Rizzuti, Mathias Louboutin, Philipp A. Witte, and Felix J. Herrmann, “Deep Bayesian Inference for Task-based Seismic Imaging”, in KAUST, 2021.
Felix J. Herrmann and Curt Da Silva, “Domain-specific abstractions for full-waveform inversion”, in SIAM Conference on Computational Science and Engineering, 2017.
Yunlin Zeng, Rafael Orozco, Ziyi Yin, and Felix J. Herrmann, “Enhancing Full-Waveform Variational Inference through Stochastic Resampling and Data Augmentation”, in International Meeting for Applied Geoscience and Energy, 2024.
Bas Peters and Felix J. Herrmann, “Generalized Minkowski sets for the regularization of inverse problems”, in SIAM Conference on Mathematical and Computational Issues in the Geosciences, 2019.
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.
Bas Peters and Felix J. Herrmann, “Intersections and sums of sets for the regularization of inverse problems”, in Canadian Mathematical Society Winter Meeting, 2018.
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.
Ali Siahkoohi, Gabrio Rizzuti, Mathias Louboutin, Philipp A. Witte, and Felix J. Herrmann, “Preconditioned training of normalizing flows for variational inference in inverse problems”, in 3rd Symposium on Advances in Approximate Bayesian Inference, 2021.
Ali Siahkoohi, Gabrio Rizzuti, Rafael Orozco, and Felix J. Herrmann, “Reliable amortized variational inference with conditional normalizing flows via physics-based latent distribution correction”, in IMAGE Workshop on Subsurface Uncertainty Description and Estimation - Moving Away from Single Prediction with Distribution Learning, 2022.
Ziyi Yin, Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “WISER: full-Waveform variational Inference via Subsurface Extensions with Refinements”, in International Meeting for Applied Geoscience and Energy, 2024.
Journal Article
Navjot Kukreja, Jan Hückelheim, Mathias Louboutin, Paul Hovland, and Gerard Gorman, “Combining checkpointing and data compression to accelerate adjoint-based optimization problems”, Euro-Par 2019: Parallel Processing, pp. 87-100, 2019.
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.
Tristan van Leeuwen and Felix J. Herrmann, “A penalty method for PDE-constrained optimization in inverse problems”, Inverse Problems, vol. 32, p. 015007, 2015.
Ali Siahkoohi, Gabrio Rizzuti, Rafael Orozco, and Felix J. Herrmann, “Reliable amortized variational inference with physics-based latent distribution correction”, Geophysics, vol. 88, 2023.
Aleksandr Y. Aravkin, Michael P. Friedlander, Felix J. Herrmann, and Tristan van Leeuwen, “Robust inversion, dimensionality reduction, and randomized sampling”, Mathematical Programming, vol. 134, pp. 101-125, 2012.
Ziyi Yin, Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “Solving multiphysics-based inverse problems with learned surrogates and constraints”, Advanced Modeling and Simulation in Engineering Sciences, vol. 10, 2023.
Ziyi Yin, Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “WISE: full-Waveform variational Inference via Subsurface Extensions”, Geophysics, vol. 89, 2024.
Ziyi Yin, Rafael Orozco, and Felix J. Herrmann, “WISER: multimodal variational inference for full-waveform inversion without dimensionality reduction”, Geophysics, vol. 90, 2025.
Presentation
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.
Abhinav Prakash Gahlot, Haoyun Li, Ziyi Yin, Rafael Orozco, and Felix J. Herrmann, “A Digital Twin for Geological Carbon Storage with Controlled Injectivity”, ML4SEISMIC Partners Meeting. 2024.
Abhinav Prakash Gahlot, Rafael Orozco, Haoyun Li, Huseyin Tuna Erdinc, Ziyi Yin, Mathias Louboutin, and Felix J. Herrmann, “Digital Twins in the era of generative AI - Application to Geological CO2 Storage”, ICL Seminar. 2024.
Yunlin Zeng, Ziyi Yin, Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “Enhancing Full-Waveform Variational Inference through Stochastic Resampling”, ML4SEISMIC Partners Meeting. 2024.

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