Biblio

Export 28 results:
Author Title [ Type(Asc)] Year
Filters: Keyword is machine learning  [Clear All Filters]
Thesis
Ben B. Bougher, Machine learning applications to geophysical data analysis, The University of British Columbia, Vancouver, 2016.
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.
Ali Siahkoohi, Gabrio Rizzuti, and Felix J. Herrmann, Uncertainty quantification in imaging and automatic horizon tracking—a Bayesian deep-prior based approach, ML4SEISMIC Partners Meeting. 2021.
Ziyi Yin, Huseyin Tuna Erdinc, Abhinav Prakash Gahlot, Mathias Louboutin, and Felix J. Herrmann, Simulation-based framework for geological carbon storage monitoring, 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.
Ziyi Yin, Mathias Louboutin, Philipp A. Witte, Ali Siahkoohi, Gabrio Rizzuti, Rafael Orozco, Henryk Modzelewski, and Felix J. Herrmann, Julia for Geoscience, Transform. 2022.
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.
Conference
Ali Siahkoohi, Gabrio Rizzuti, and Felix J. Herrmann, Weak deep priors for seismic imaging, in SEG Technical Program Expanded Abstracts, 2020, pp. 2998-3002.
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.
Ali Siahkoohi, Gabrio Rizzuti, and Felix J. Herrmann, Uncertainty quantification in imaging and automatic horizon tracking—a Bayesian deep-prior based approach, in SEG Technical Program Expanded Abstracts, 2020, pp. 1636-1640.
Ali Siahkoohi, Dirk J. Verschuur, and Felix J. Herrmann, Surface-related multiple elimination with deep learning, in SEG Technical Program Expanded Abstracts, 2019, pp. 4629-4634.
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, Rajiv Kumar, and Felix J. Herrmann, Seismic data reconstruction with Generative Adversarial Networks, in EAGE Annual Conference Proceedings, 2018.
Ben B. Bougher and Felix J. Herrmann, Prediction of stratigraphic units from spectral co-occurance coefficients of well logs, in CSEG Annual Conference Proceedings, 2015.
Gabrio Rizzuti, Ali Siahkoohi, and Felix J. Herrmann, Learned iterative solvers for the Helmholtz equation, in EAGE Annual Conference Proceedings, 2019.
Ziyi Yin, Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann, Learned coupled inversion for carbon sequestration monitoring and forecasting with Fourier neural operators, in International Meeting for Applied Geoscience and Energy Expanded Abstracts, 2022.
Ali Siahkoohi, Rajiv Kumar, and Felix J. Herrmann, Deep-learning based ocean bottom seismic wavefield recovery, in SEG Technical Program Expanded Abstracts, 2019, pp. 2232-2237.
Ali Siahkoohi, Mathias Louboutin, Rajiv Kumar, and Felix J. Herrmann, Deep Convolutional Neural Networks in prestack seismic–-two exploratory examples, in SEG Technical Program Expanded Abstracts, 2018, pp. 2196-2200.
Ben B. Bougher and Felix J. Herrmann, AVA classification as an unsupervised machine-learning problem, in SEG Technical Program Expanded Abstracts, 2016, pp. 553-556.

Pages