Biblio
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Author Title [ Type
] Year Filters: Keyword is machine learning and Author is Gabrio Rizzuti [Clear All Filters]
, “Abstractions for at-scale seismic inversion”, in Rice Oil and Gas High Performance Computing Conference 2022, 2022, p. Thursday Workshop: Devito Training and Hackathon.
, “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.
, “Learned iterative solvers for the Helmholtz equation”, in EAGE Annual Conference Proceedings, 2019.
, “Uncertainty quantification in imaging and automatic horizon tracking—a Bayesian deep-prior based approach”, in SEG Technical Program Expanded Abstracts, 2020, pp. 1636-1640.
, “Weak deep priors for seismic imaging”, in SEG Technical Program Expanded Abstracts, 2020, pp. 2998-3002.
, “Learned multiphysics inversion with differentiable programming and machine learning”, The Leading Edge, vol. 42, pp. 452-516, 2023.
, “Adjoint operators as summary functions in amortized Bayesian inference frameworks”, ML4SEISMIC Partners Meeting. 2022.
, “Julia for Geoscience”, Transform. 2022.
, “Uncertainty quantification in imaging and automatic horizon tracking—a Bayesian deep-prior based approach”, ML4SEISMIC Partners Meeting. 2021.