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2012
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.
2015
Tristan van Leeuwen and Felix J. Herrmann, “A penalty method for PDE-constrained optimization in inverse problems”, Inverse Problems, vol. 32, p. 015007, 2015.
2017
Felix J. Herrmann and Curt Da Silva, “Domain-specific abstractions for full-waveform inversion”, in SIAM Conference on Computational Science and Engineering, 2017.
2018
Bas Peters and Felix J. Herrmann, “Intersections and sums of sets for the regularization of inverse problems”, in Canadian Mathematical Society Winter Meeting, 2018.
2019
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.
2021
Ali Siahkoohi, Gabrio Rizzuti, Mathias Louboutin, Philipp A. Witte, and Felix J. Herrmann, “Deep Bayesian Inference for Task-based Seismic Imaging”, in KAUST, 2021.
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.
2022
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.
Ali Siahkoohi, Gabrio Rizzuti, Rafael Orozco, and Felix J. Herrmann, “Low-cost uncertainty quantification for large-scale inverse problems”, ML4SEISMIC Partners Meeting. 2022.
Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “Normalizing flows for regularization of 3D seismic inverse problems”, ML4SEISMIC Partners Meeting. 2022.
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.
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.
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, 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, “Solving PDE-based inverse problems with learned surrogates and constraints”, HotCSE Seminar. 2023.
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.
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, 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.
Yunlin Zeng, Ziyi Yin, Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “Enhancing Full-Waveform Variational Inference through Stochastic Resampling”, ML4SEISMIC Partners Meeting. 2024.
S. Zeng, Huseyin Tuna Erdinc, Ziyi Yin, Abhinav Prakash Gahlot, and Felix J. Herrmann, “Enhancing Performance with Uncertainty Estimation in Geological Carbon Storage Leakage Detection from Time-Lapse Seismic Data”, ML4SEISMIC Partners Meeting. 2024.
Richard Rex, Yunlin Zeng, Ziyi Yin, Rafael Orozco, and Felix J. Herrmann, “FNO-charged ASPIRE”, ML4SEISMIC Partners Meeting. 2024.
S. Zeng, Rafael Orozco, Huseyin Tuna Erdinc, and Felix J. Herrmann, “Image Impeccable Challenge: An Effective Machine Learning Denoising Method for 3D Seismic Volumes”, ML4SEISMIC Partners Meeting. 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.

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