Biblio
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] Title Type Year Filters: Keyword is machine learning [Clear All Filters]
, “Using the scattering transform to predict stratigraphic units from well logs”, CSEG Recorder, vol. 41, pp. 22-25, 2016.
, “Machine learning applications to geophysical data analysis”, The University of British Columbia, Vancouver, 2016.
, “Prediction of stratigraphic units from spectral co-occurance coefficients of well logs”, in CSEG Annual Conference Proceedings, 2015.
, “AVA classification as an unsupervised machine-learning problem”, in SEG Technical Program Expanded Abstracts, 2016, pp. 553-556.
, “Uncertainty-aware machine-learning enabled velocity-model building with Devito”, in 18th Annual Energy High Performance Computing Conference 2025, RICE, 2025, p. 4th Annual Devito User and Developer Workshop.
, “Digital twins in the era of generative AI”, The Leading Edge, vol. 42, 2023.
, “Learned multiphysics inversion with differentiable programming and machine learning”, The Leading Edge, vol. 42, pp. 452-516, 2023.
, “Abstractions for at-scale seismic inversion”, in Rice Oil and Gas High Performance Computing Conference 2022, 2022, p. Thursday Workshop: Devito Training and Hackathon.
, “Low-memory stochastic backpropagation with multi-channel randomized trace estimation”, TR-CSE-2021-1, 2021.
, “Accelerating innovation with software abstractions for scalable computational geophysics”, in International Meeting for Applied Geoscience and Energy Expanded Abstracts, 2022.
, “Adjoint operators enable fast and amortized machine learning based Bayesian uncertainty quantification”, in SPIE Medical Imaging Conference, 2023.
, “Adjoint operators as summary functions in amortized Bayesian inference frameworks”, ML4SEISMIC Partners Meeting. 2022.
, “Normalizing flows for regularization of 3D seismic inverse problems”, ML4SEISMIC Partners Meeting. 2022.
, “Seismic Velocity Inversion and Uncertainty Quantification Using Conditional Normalizing Flows”, in AGU Annual Meeting, 2021, p. U12A-03.
, “Learned iterative solvers for the Helmholtz equation”, in EAGE Annual Conference Proceedings, 2019.
, “Seismic data reconstruction with Generative Adversarial Networks”, in EAGE Annual Conference Proceedings, 2018.
, “Weak deep priors for seismic imaging”, in SEG Technical Program Expanded Abstracts, 2020, pp. 2998-3002.
, “Deep Convolutional Neural Networks in prestack seismic–-two exploratory examples”, in SEG Technical Program Expanded Abstracts, 2018, pp. 2196-2200.
, “Uncertainty quantification in imaging and automatic horizon tracking—a Bayesian deep-prior based approach”, in SEG Technical Program Expanded Abstracts, 2020, pp. 1636-1640.
, “Uncertainty quantification in imaging and automatic horizon tracking—a Bayesian deep-prior based approach”, ML4SEISMIC Partners Meeting. 2021.
, “Surface-related multiple elimination with deep learning”, in SEG Technical Program Expanded Abstracts, 2019, pp. 4629-4634.
, “Deep-learning based ocean bottom seismic wavefield recovery”, in SEG Technical Program Expanded Abstracts, 2019, pp. 2232-2237.
, “Uncertainty-aware time-lapse CO$_2$ monitoring with learned end-to-end inversion”, ML4SEISMIC Partners Meeting. 2022.
, “Learned coupled inversion for carbon sequestration monitoring and forecasting with Fourier neural operators”, in International Meeting for Applied Geoscience and Energy Expanded Abstracts, 2022.
, “Uncertainty-aware time-lapse monitoring of geological carbon storage with learned surrogates”, in Engineering Mechanics Institute Conference, 2023.