Biblio
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, “Extended source imaging –- a unifying framework for seismic and medical imaging”, in SEG Technical Program Expanded Abstracts, 2020, pp. 3502-3506.
, “Extending the search space of time-domain adjoint-state FWI with randomized implicit time shifts”, in EAGE Annual Conference Proceedings, 2017.
, “Fast and reliability-aware seismic imaging with conditional normalizing flows”, in Intelligent illumination of the Earth, 2021.
, “Fast neural FWI with amortized uncertainty quantification”, in International Meeting for Applied Geoscience and Energy, 2023.
, “Generative Seismic Kriging with Normalizing Flows”, in International Meeting for Applied Geoscience and Energy, 2023.
, “InvertibleNetworks.jl - Memory efficient deep learning in Julia”, in JuliaCon, 2021.
, “Large-scale workflows for wave-equation based inversion in Julia”, in SIAM Conference on Computational Science and Engineering, 2017.
, “Learned coupled inversion for carbon sequestration monitoring and forecasting with Fourier neural operators”, in International Meeting for Applied Geoscience and Energy Expanded Abstracts, 2022.
, “Learned non-linear simultenous source and corresponding supershot for seismic imaging.”, in International Meeting for Applied Geoscience and Energy, 2023.
, “Learned wave-based imaging - variational inference at scale”, in Delft, 2021.
, “Leveraging symbolic math for rapid development of applications for seismic modeling”, in OGHPC, 2017.
, “Low-cost time-lapse seismic imaging of CCS with the joint recovery model”, in SEG Workshop on Geophysical Challenges in Presalt Carbonates; virtual, 2021.
, “ML@scale using randomized linear algebra”, in Microsoft, 2021.
, “Monitoring Subsurface CO2 Plumes with Sequential Bayesian Inference”, in International Meeting for Applied Geoscience and Energy, 2023.
, “The Next Step: Interoperable Domain-Specific Programming”, in SIAM Conference on Computational Science and Engineering, 2023.
, “Normalizing Flows for Bayesian Experimental Design in Imaging Applications”, in SIAM Conference on Uncertainty Quantification, 2024.
, “Optimised finite difference computation from symbolic equations”, in Python in Science Conference Proceedings, 2017, pp. 89-96.
, “The power of abstraction in Computational Exploration Seismology”, in Smoky Mountains Computational Sciences and Engineering Conference, 2018.
, “Preconditioned training of normalizing flows for variational inference in inverse problems”, in 3rd Symposium on Advances in Approximate Bayesian Inference, 2021.
, “Raising the abstraction to separate concerns: enabling different physics for geophysical exploration”, in SIAM Conference on Computational Science and Engineering, 2017.
, “Refining Amortized Posterior Approximations using Gradient-Based Summary Statistics”, in 5th Symposium on Advances in Approximate Bayesian Inference, 2023.
, “Regularizing waveform inversion by projections onto convex sets”, in Inaugural Full-Waveform Inversion Workshop, 2015.
, “Seismic Imaging with Uncertainty Quantification: Sampling from the Posterior with Generative Networks”, in SIAM Conference on Imaging Science, 2020.
, “Seismic Velocity Inversion and Uncertainty Quantification Using Conditional Normalizing Flows”, in AGU Annual Meeting, 2021, p. U12A-03.
, “Serverless seismic imaging in the cloud”, in Rice Oil and Gas High Performance Computing Conference 2020, 2020.