Home /Biblio

Biblio

Export 31 results:
Author Title [ Type(Asc)] Year
Filters: Keyword is Normalizing flows  [Clear All Filters]
Unpublished
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.
Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann, “ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems”. 2024.
Presentation
Ziyi Yin, Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “WISE: Full-waveform Inference with Subsurface Extensions”, ML4SEISMIC Partners Meeting. 2023.
Ziyi Yin, Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann, “Uncertainty-aware time-lapse CO$_2$ monitoring with learned end-to-end inversion”, ML4SEISMIC Partners Meeting. 2022.
Rafael Orozco, Mathias Louboutin, Peng Chen, and Felix J. Herrmann, “Uncertainty quantification so what? Leveraging probabilistic seismic inversion for experimental design”, ML4SEISMIC Partners Meeting. 2023.
Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “Towards generative seismic kriging with normalizing flows”, ML4SEISMIC Partners Meeting. 2023.
Ziyi Yin, Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “Solving PDE-based inverse problems with learned surrogates and constraints”, HotCSE Seminar. 2023.
Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “Normalizing flows for regularization of 3D seismic inverse problems”, ML4SEISMIC Partners Meeting. 2022.
Ali Siahkoohi, Rafael Orozco, Gabrio Rizzuti, Philipp A. Witte, Mathias Louboutin, and Felix J. Herrmann, “Multifidelity conditional normalizing flows for physics-guided Bayesian inference”, ML4SEISMIC Partners Meeting. 2021.
Ali Siahkoohi, Gabrio Rizzuti, Rafael Orozco, and Felix J. Herrmann, “Low-cost uncertainty quantification for large-scale inverse problems”, ML4SEISMIC Partners Meeting. 2022.
Ziyi Yin, “Introduction to Seismic Laboratory for Imaging and Modeling”, CSE Student Recruiting Event. 2023.
Ziyi Yin, Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “Generative AI for full-waveform variational inference”, Georgia Tech Geophysics Seminar. 2024.
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.
Felix J. Herrmann, “Act normal that's crazy enough — an overview of seismic inversion with normalizing flows and surrogate modeling”, Scientific Computing, Applied and Industrial Mathematics (SCAIM) Seminar. 2023.
Journal Article
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.
Ali Siahkoohi, Gabrio Rizzuti, Rafael Orozco, and Felix J. Herrmann, “Reliable amortized variational inference with physics-based latent distribution correction”, Geophysics, vol. 88, 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.
Felix J. Herrmann, “Digital twins in the era of generative AI”, The Leading Edge, vol. 42, 2023.
Conference
Ali Siahkoohi, Rafael Orozco, Gabrio Rizzuti, and Felix J. Herrmann, “Wave-equation based inversion with amortized variational Bayesian inference”, in EAGE Annual Conference Proceedings, 2022, p. Session 2: Velocity model building and imaging (different domains).
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.
Yuxiao Ren, Philipp A. Witte, Ali Siahkoohi, Mathias Louboutin, Ziyi Yin, and Felix J. Herrmann, “Seismic Velocity Inversion and Uncertainty Quantification Using Conditional Normalizing Flows”, in AGU Annual Meeting, 2021, p. U12A-03.
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.
Rafael Orozco, Abhinav Prakash Gahlot, Peng Chen, Mathias Louboutin, and Felix J. Herrmann, “Normalizing Flows for Bayesian Experimental Design in Imaging Applications”, in SIAM Conference on Uncertainty Quantification, 2024.
Ali Siahkoohi and Felix J. Herrmann, “Learning by example: fast reliability-aware seismic imaging with normalizing flows”, in SEG Technical Program Expanded Abstracts, 2021, pp. 1580-1585.
Felix J. Herrmann, Ali Siahkoohi, Rafael Orozco, Gabrio Rizzuti, Philipp A. Witte, and Mathias Louboutin, “Learned wave-based imaging - variational inference at scale”, in Delft, 2021.

Pages