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Filters: Keyword is Inverse problems and Author is Rafael Orozco  [Clear All Filters]
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”. 2024.
Y. Zeng, Rafael Orozco, Ziyi Yin, and Felix J. Herrmann, “Enhancing Full-Waveform Variational Inference through Stochastic Resampling and Data Augmentation”. 2024.
Ziyi Yin, Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “WISE: full-Waveform variational Inference via Subsurface Extensions”, Geophysics, 2024.
Ziyi Yin, Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “WISER: full-Waveform variational Inference via Subsurface Extensions with Refinements”. 2024.
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, 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.
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.
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.