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I
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”. 2023.
F
Ali Siahkoohi, Gabrio Rizzuti, Philipp A. Witte, and Felix J. Herrmann, “Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows”, Georgia Institute of Technology, TR-CSE-2020-2, 2020.
Ali Siahkoohi, Rafael Orozco, Gabrio Rizzuti, Philipp A. Witte, Mathias Louboutin, and Felix J. Herrmann, “Fast and reliability-aware seismic imaging with conditional normalizing flows”, in Intelligent illumination of the Earth, 2021.
E
Ziyi Yin, Rafael Orozco, Philipp A. Witte, Mathias Louboutin, Gabrio Rizzuti, and Felix J. Herrmann, “Extended source imaging –- a unifying framework for seismic and medical imaging”, in SEG Technical Program Expanded Abstracts, 2020, pp. 3502-3506.
D
Gabrio Rizzuti, Mathias Louboutin, Rongrong Wang, and Felix J. Herrmann, “A dual formulation of wavefield reconstruction inversion for large-scale seismic inversion”, ML4SEISMIC Partners Meeting. 2021.
Gabrio Rizzuti, Mathias Louboutin, Rongrong Wang, and Felix J. Herrmann, “A dual formulation of wavefield reconstruction inversion for large-scale seismic inversion”, Geophysics, vol. 86, p. 1ND-Z3, 2021.
Gabrio Rizzuti, Mathias Louboutin, Rongrong Wang, Emmanouil Daskalakis, and Felix J. Herrmann, “A dual formulation for time-domain wavefield reconstruction inversion”, in SEG Technical Program Expanded Abstracts, 2019, pp. 1480-1485.
Gabrio Rizzuti, Mathias Louboutin, Rongrong Wang, Emmanouil Daskalakis, and Felix J. Herrmann, “A dual formulation for time-domain wavefield reconstruction inversion”, in SIAM Conference on Mathematical and Computational Issues in the Geosciences, 2019.
Ali Siahkoohi, Gabrio Rizzuti, and Felix J. Herrmann, “A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification”, GT SEG Student Chapter. 2020.
Ali Siahkoohi, Gabrio Rizzuti, and Felix J. Herrmann, “A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification”, in EAGE Annual Conference Proceedings, 2020.
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, and Felix J. Herrmann, “Deep Bayesian inference for seismic imaging with tasks”, Geophysics, vol. 87, pp. 281-302, 2022.
A
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, 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, and Felix J. Herrmann, “Adjoint operators as summary functions in amortized Bayesian inference frameworks”, ML4SEISMIC Partners Meeting. 2022.
Mathias Louboutin, Philipp A. Witte, Ali Siahkoohi, Gabrio Rizzuti, Ziyi Yin, Rafael Orozco, and Felix J. Herrmann, “Accelerating innovation with software abstractions for scalable computational geophysics”, in International Meeting for Applied Geoscience and Energy Expanded Abstracts, 2022.
Mathias Louboutin, Ali Siahkoohi, Ziyi Yin, Rafael Orozco, Thomas J. Grady II, Yijun Zhang, Philipp A. Witte, Gabrio Rizzuti, and Felix J. Herrmann, “Abstractions for at-scale seismic inversion”, in Rice Oil and Gas High Performance Computing Conference 2022, 2022, p. Thursday Workshop: Devito Training and Hackathon.

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